{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "from sklearn.datasets import make_blobs\n",
    "\n",
    "np.random.seed(0)\n",
    "\n",
    "batch_size = 45\n",
    "centers = [[-0.1, 1.7], [1.5, 0], [1.8, 1.5]]\n",
    "n_clusters = len(centers)\n",
    "X, labels_true = make_blobs(n_samples=[3042, 4564, 2394], centers=centers, cluster_std=0.4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 数据图形"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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z33fms/Y+78r1riXcMIL8ehhsTw+rp76rwlXPDQtXO1XA64W1eKnE9lXVroWmJTId6l9AVbNSNfkRC7Zq//7nz6XwV68lrr9mb7GW9sYuLW7uZi1+3mbtlhf/KY+bvGy3NvL3Xy8Yap/S3til/eSt3dKjxpNQEhGi7hZET1qvu92Du3npiLP1pMF29hz1ep6iVN21KxZoPRetaa4Lnf4aKsXiaaETn6keQ+3tHtztCtR+imdWvZ4nqqejsdJ/157W7m5R6apdpL02r2XcEIL8elo5Na1rRjRVgHnitUdeNFC645xVjVzPmz+6IkubtHSXC0+p1+xUDf98XbM0WgphKxYZ1etFGEHf+axAu/dPO7XhL22Vx6uuj0J4qzysO+8V9aUUofruBLknTVzfhictsCNPFXfndzS3+gXCnbbbmTbUHZK7BcwT3SFSI4i50i8I+jb0c+BpkXN3X/p50/dDtc24W6j0besXCE82A/V7d8+/u3G5XmRFZ3HVBDnQH9gJHAOOAr/s6JxrRSO/0ra6cr4nYSQeZpXHdnes0HJVjV1tV69lqUJBCFNVCx+9cJts7ydvOT1HVGNnwm//qd33p8+0Yb/PkBq00OrVXOZCcKS9scutP/qjK7K0e/+0U4u9yLdPXrZbG7Fgq8vuQp9bRaWT2nvx9Zqguxfbk0BtTxPtaG7b06bbWwC6omG6u4an9oQAHa7koxfz6o4/F1SZumDohaO6uKqxCOKZUudP7Y94jtTFRP+MurODiPPdeeHox11PNXkak+4wSl9r8CTIuyPXigP4T03TbgHuAJ4xGAzJ3dCuW3RXmagrzdHQlfP1eSpE+TRx7syxscxZ+xUF5fUAVDW0kFdWR15ZncyfEh7kj8noQ0JUMOlTh8u2qxqcbSRFh5A+dTgrM4sB5zjNGhcPQLXVRvqOE4QHfZ1vZMHEFIICjNQ02ik438CMMbGYjD7M35DDqqxiYsICCfT3pW+PQJptrTz2nTimjOrPugOnmZuaJP8GsLY4KKlulNedM2EQSdEhRAb7Mzc1iZBAEynRIcSEmwEYGBFEmMXkMkZTRvWXf4dZTKx8/HbnvV4sGyfaFnk4RLk68Z3J6CNL16ml4NyVhxOftzeX7T1nnvKBqNdv7xrucoWI3DHu+q3ev7vzIoP9ee6eRJKjQwg1+8nx9fP1YW5qkksbSdEhzE1NwmR05sMRbYprJUWHMGfCIBZuzmXOmkM8veoAT394kOnv7KWqoYW5qUlYWxw8/cFBMgsqeX59tkvf5z+QzHP3JGIyXipawoP8XcoFinw76njYHG0uOXnU90SMiXi2xN/uxthdGTv9M3Mj4YoFuaZpZZqmHbz4dz1OzbzvlbZ7tdFecp6unN/ZY+dMGCSFydzUJJlQas6aQ1JwjU2IYG5qEgs35zL93b3M++gwNkebFNYmow9VDS0s3VnAI3/JYsvhMmau+FLWdRybECH7lFdWx5Lt+VhbHCzdWcCcCYPk9aa/u5cVu4uYNS6eFbuLiA4NZHRcTynMZ4yJpbrJjqaBo00j73wD//VRNs//PZuGZgfVVhsvbsqh2mqjqMJKmMXEK2lDWJlZTF5ZnduanS/8+y0s3VmAyejDc/ckurzAVlsrL2w4wpw1h8gsqGTmii+pttpkfU+9ABYCQB1TkZBJreXZ2RdWnZ/OwlOiKzH2KoSwFXOjCnRxbXXMVGHUnsIgzssrq2NlZjGzxyewfFehFKJicRPKg2hfCMqlOwukcFPvQygN8x9IZtmMUax+8g7enD6SpOgQwoP8sbdpgAY4Be/CzblU1LfIpGtLdxbIJGliIdFfR4yh/h10twB4Gnf9HLhrTx1r9Zm54eBOTb/cH2AAUAKEuPluFrAf2B8TE3P19yDdDE8cXGc4e5UyUbffqpFTv4UU3LbewKVSLeq2V21TbG+H/36rlvbGLkmZqBz19OWZ2jufFWjDXsrQhr6Uoa3ZW6yNWvA13aJurdfsLXZu2S9u3YVXy71LPpNBR5rm6vEgttlpS7/Qhl2MABWGT3U8xfZbtKsaa9UUAvrx7Ij60IeLt3d8Z47pDMS86PPDu3MFbI+H1/PWnrh0PYWkadolc6cer7eJ6NMdu6OhxN+qZ5MIOBP3pz6n6nOrBnqJ7y7HbtDe552Zk66ecy0DD9SKwfndlcNgMAQBnwOvaJr29/aOHT16tLZ///5uuW5X0ZnUnfpjhVbkLjUtdEz3CI1o1rh4VmYWM2fCIMKD/Hl+fTZTRvVndFxPt+3kldW5bDPBqWGo5zc0OwgKMDJrXDxhFhMz3s2iX08zrz44hKIKK3GRFhZuzsVqa6Wkysork4awKquYyoYWCiutzL13MJuPlBFmMTFrXDw1jXZe+vgo6VOHMzYhQmpZiycPY+PBM+zMryC3tBaHBo0tDv4waQgx4WaOnq1l8bbj/HnqCDZmlzJzbCxLdxZgbXGAwYCfjwF7axtna5p4/4kxhAf5U9XgTNE7a1w8y3cVYm1xUHC+gbn3JbH+4BlOVVn59T2D2ZlfwcJJKXJnIjQrdYuujl9FfQtPrzqAyehD+rQR7c6RmFu1vStFZkElYxMiXOZR33ZHNI6alnhuatIlFMLz67Plrk6cn1dWx/R39xITZsbibyR92gj5/FY1tFwy5kt3FgBOrToowCjbE22K60wZ1Z8XN+Xw+rQRJEQFU9XQ4tIfsQsTYyieGZujjfkPJMtnWKV43L1P7sbA3fvn6X3sLnRFRnzTMBgMBzRNG63/vFvykRsMBj/gI+CDjoT4t4nL5bXbyy/emXYEnbJ8V6GLwGhodrAqq5iqhq+3voImqahvYeHmXJ5fn01Beb18qedMGCRzhs8aF4/J6ENqcm9WZhY7Odq0FMLMflRbbfxmw2HAmZ/cYvKlT2gAb//rJPbWNkIC/BgcFcR3EyMllxpmMbExu5SXfnirpEkWbs7F5mhjf9EF/rg1jxljYvnDj4ay+MGhjIoNo6y2iRnvZvHq1uPEhZuJi7QwOiaU5bsKmTEmFou/kYdG9ycowMhTdw3k9WkjKKqw8vz6bOZ9dJiGZgcJUcFMGdWfX01IJDbczKJteTx3TyLvPzGGqWNimDNhEFUNLTzylywWbs4lbVgfSUUInlbQMgJBAUbmP5B8CTeuh8rpdwWeniFBc6jfuxPiIre7u/zaAosnD5NUm/pciOcJcOHXw4P8GRgRhJ+vD/bWNtnenDWHJOcNTsG9fFch8x9IZv4DyVIREOOk9sna4mDdgdMsmJjC0p0FPL8+Wwpm0Z+k6JBL+OrFk4eRPm2EVDjE8WI+9Py/ev/iXtV+6CmRziwCl4PrNb/5FQtyg8FgAP4CHNM0bcmVd+nqoSu8uP7YzvBxeoiHIrOgUj78qoZtMvpgc7RRbbUBsL/oAo/8JYs5aw5J7XPKqP4s2Z4vuXJxfkF5vdR4X9t+nJljYwFYd+C0NHJaW1qpttoID/Jn9vgEjD4+lFQ38th34nj8zjjMJiPVVhsnKxuottpYlJHHzLGx3D80mjkTBlFUYZVGsbomO61tcPxcHb/bcIQVu4v48Yh+LN1ZQP9wM6+kpfDnh0byn+u+4uUteZRWN7JidxG1TTZe236c1OTevLgph5c+Psqzaw9xZ3w4Jyut8r6fXXOQRVuP8+8p0dzSO4SEqGDCg/zJLKgkfccJAN5/YgzzH0hmY3apFO7PrjnElFH9sTnaeHbNIclH67XY9ubIHaff0TnuXnaVh20P4tkRxlEBwSPnldW5PANHSmtkkRBhXBRjMnNsrIu9YdmMUSyclILF3wh8bQyfPT5BCndR9CMpOkQaP5fvKrxEaFY1tKBpzh1BqNkPk/Fr46lYQIUCIt6DzIJKZrybJa8roCorYgz0hl6x6Ijzxdg8vz6bRRl5LjaE9ubmSoTxldrO9H35ptAdGvmdwCPA3QaD4auLPz/ohnavCq7EoHU53wuPlKqGlksqpMx/wOncs3RnAVNG9WdjdimvTxsht6M2Rxt/3VNEYYXTq0Ro4uLFA3j1x0N5/4kxcstrc7SxKCOPMIuJ9x5zen48vz6bl/+Zi8now9N3DWRVVjG/2XCY4+fqqWm0c0tvp8CzOdpYurOAtVklzPvoMM+uPURqcm+W7ixg9b4Sgvx92X2yiv7hFgBCAv0IMPlSbbWx6XApAI6LwuL+lGin4Uoz8Pq0EdydHMWCiSmEBPiR2CsIgCabg8fvjCMu0kJ8hIWmFjuLtx1nxphYqhqcL/UvVh+SGjggtb/wIH/Cg/xJjApmdFxPls0YxftPjJHVkjwJZ70hUsyRO+24vXl197KrAtqToFehauViwRKLwLGLu6Fqqw1fnAZiUTlJjEFBeT0rM4vlIi4EnBDOgkYBqGm0c/J8A79cfZCnPzggBa0wbgpFQQjNLYfL+M91X1FY0UB2SY1cMMXiOmftV0wZ1d/lma6ob2H5rkLiI53Ph0oN6SlCdezFXAmvl1U/c1JvqiFbvY4ng6Uq5D1p/J1Bdwnxb1Kz7zaOvCv4Njnyq4H2uHLBT6p8blXD12XO/ndHPpqG3N4mRAUzf0OO5JjnP5BMtdUmBfKscfGMTYhwuabKSY5PjOTVbccZ0S+UZTNGERnsz5bDZTy79hDxERYq6luYe18SMeFm5m84Qs8gf341IVEKhEUZeRwtq6NPjwCC/I389I4BrN5XgqOtjRd+kEyYxSS1d4u/kZpGG7PHDyLU7CcXk1+uPsifHxpJdkkNL2w4whsPjWTdgdNUN9rx8zHgaGujpKqRiGB/5vxbIit2F5F/vp7EXsFSsC/cnCsXOsHtpu84IbW0OWsOXcJ/q5qhOs4qd/vIX7KkwAfkZ4lRwcx/ILlDLb6z/Kn+uMyCSlZmFrssAOIYPccs+iUgxkLcv9CIn11ziIdvjyH7bK0LXy4oMZPRR+7Olu8q5M74cN78rIA2YO2ssQAufHn6tBHSBfapD/bT2NLKvPuS2JpbTqPNQajZhL21DU2D+5Kj2F1Y5SJg9TadOWsOybKDej5f3P/8DTmkDevD/UOjXcZBvVf1eLE46JUiAdUeodoSvg3O+2pw7VeVI7+ZIR4W1b1L/W7+hhzpAiaOXZSRR9qwPizfVYimObWHualJrMx08uVzJgyShqhqq036hs8aF88vVju5YKGtCO0zNbk3NkcbW3PLiQ0LlAKvor6F+4dG8/rUEbz0w1uJDPbnf7Yd5+jZWgoqGzlaVkeYxcTCSSmMTYjgnZm3MffewZypbnK6BW48wvHyWvLO1VNS1ciijDyWbM+npLqR8YmRnKlp4u1/neSpVQckBxsRHMC8jw6zel8Jgf5GQs1+pCb35syFRp67J5E/PjiUlycNIdBk5Df/OEyTrZV+oc4+j47ryfwNORw7V0dRhZN6EWMoDJ5VDS0cO1dHVYOr4FY1oILyerlYCo1PaPCqsEmKDuH9J8aQPm1Ep4R4Z7Qs1UgnePxn1xySmrOAqjEKA7ZAeJA/izLypBAXWrg4Z/muQsItfrz5+UlJzYlrz/7ggHxelu4sYOnOAhqaHezMr2DZw6P4v4dHyfarrTaWbM8HnBTXnLVfOcclKoSk3sHc2rcHJyrqsfgbmT0+AU2DY+W1pH96goZmB4CMeZi54ku5EICTOlT7JvqnYubYWF76+KjLjkS9V3GOGFN3tT/VtoU75rWAb3Lx8AryK4TeL1x90VXfYXWbOTc1iY3ZpdJYCchADEEhAMwYEyu9XAASooLp3zOQpTsLXF6ImWNj+Z9tx6lutFHXZKOkuomiCivPfHBAcqqrsopZsj2f8/Ut/Ne9g7m1bw9+d38Sw/uFym2sQN8wM2Z/X0ID/Zj9/QT69DAzOCqYjNxzpCb3ZtmMUbz50Ei25pZjAL6fGEmTzcH4xEjCg/yZOLQPRRf575ieZpZsz+e17cf5r3sHkxAVzKKMPFZlFdPUYiciyB+jr4Ez1U3y+kEBRubem8TvNhxxGukubqULyuulj/ktvUNcBJ861nlldcxZ+xUzx8ZK33qx8AktXoUIMOnMXLujVNwt3iKYa86aQyzdWcCAcAthFpOcDyGc5qw5xMPv7OXFjTkuHLJ4VlSjpRDikcHOYK///mEK7z12u6RR5m/IIX37cQoqG7ktNowwi0nGBSyclILJ6OOMWbioGKQm93Z51jZml5I+dTgJUcH8akIiPQKdQVuDIoNZkJYiF/zeQQE021u5c2A4VQ0tTH93LwDpU4ezfFehfNaFl5YwzAqOX1VqEqKCeemHtxJmMbk1OusVpfaM13qffDW+wNN83SgwftsduN4htADxgrurCi4eHJUeUI1cizLypHFOfG5ztLkYLoWLnNnknLKC8nrJkc6ZMIj/uCueP27JY0j/UF6fOoK6JjuFFVb+697BUuA9d08iS7bns2Z/CTmldQzvF+rS38yCSv53Rz4nzzfQt0cAAO/uLqKhpZXf3Z9EcIAf8zc5OciYcDNBAUZ+k3oLO/MreOb7Cbz1+Uk2fFXKqeoGfPHhodti2HS4lNnjEwBYmVnM3clRzE1N4ov8Cv54kb/9TWoSSz8vILukhqljYuSiuOlwqdRGhTfIk9+NY2xCBAlRwZJGEAuROr5qBKH+RRaua+6+cze/7QWhuHOFE3+744ZFAI3J6CM9OwRfLYKgVMrhRHk98zfkOBe31CS5y3jmw4NggFfShvDiphwGhFt4/M445m/MoX9YIKlDoknfcYIpo/ozf2MObzw0wuUZ23jwDIu2HifA5MPAiCBWZRVL24zYWYlgMoCiCisvfXyUJ78bx4UmO1NH9+etfzntNBdjg0iICmbx5GHyfgQ1qI6BPtK0oLyeFzYeoU3TuDW6hxwPVTt3R8t4gl6b78x83QjwcuTdAHdcmDuOVPhl6/2fhUAWwkUYqe6MD2d3YZWLP25VQwtFFVZe2HgEgwbPX/S5tre2UVRp5f9mjKKkqpEXPz7K5JF92XHsPOlTh/PKJ7m89pPhhAf5s7/oAnVNdmLCzTJUvtpq49k1h+gbGshDt8WQkXuOWePieWlTDsfPWxkYYSY4wI8mm4MzNU34+/nySprTJ33i0D5k5J6j9GKY/rm6Fh77zgCyz9ZS3WjHYvJlxphYRsf1lN42R0priLT4M2vcQO5OjmLa23s4Xd3EyosGWsEDC3vA/A05jE+MZP6mHFY+djuA9JuPj7SwIC1F8r2qD7en+QLPvsyq9qs/pr25Vo/Xty/mXSw8qt1EcNr55fWSvxd2j4Zmh2xPf774bG1WCesPnmHhpBSqrTbJd4tn6cWNOfj5Oj2kls0YJb2E+oYG8vPvJTAsJlTy2OLZEykY7owPZ9uxciz+RlKTe/Pa9uOEBBjp3SOQ22LD+ODLEn59z2DuTo6SPuerspxRps+uOcTr00ZIZUO9hjBKi7GBrz26xCK27sDpTvHbnXn/9PN0vQpxL0d+BehoK+bugVFzUIitvuABVRcpVauGr12tUpN78z/b80lN7i3pF+EPvO7AaV5JG8LLk4aw6XApeefqwGDg/2aMIsxiYsmOfH56Rwzbcst56Ye3UtNo52hpPfM+OsynueX8YvVBXt6Sy6xVB/jJ23v4yf/tZsn2fJ4aF4+frw/rD56R2+E/PzSSOXcncMFq42SllftTorG1avx0jJPvPVRygcVbnYvOuboWSuuaiQgy8dfMU878KZpGTaONZ9ce4tPccuas/YrbYsNAM1BhbWHT4VL2F13ggtXOwolfC8Ath8uYs/YrOYYLJ6UQEujHsH6h1DTaefRv+6i22liYloLQRYR/tJgvT1ypEIKehLi6jVc9JDxx5Kr2p9I4qhCfueJLthwuI33HCalxiucgfccJ5j+Q7CLEhSa6bIaTzxbcr4gtEEIvr6yORdvyOFpWy8LNuYBTkxZYlJHHryYkMnt8AqeqrBSU17Mqq5jYcAsVDS28ssXpGTNrXLxLsNCqrGJSk3vz6tbj2BxtzE1Nkp5HNY12ahvt7D5ZRa9gfzYdLqWgvB5ri4O5/8gm52wt4HQXHZsQIfl/IcRFWgkB4QapeqWsO3Aam6PtkrnRw92cdPTZ1RLiXXFf7W54BXkHaM/A1d6ECDfAinqn9iGSQKkv+pwJg2SQkKAHBIc+dUwMf3v0NqaOiXHZos9/IFlqS6uyipkxJhZfXwNoGmEWE0nRIbz0w1spqLDSLyyQULMfoWY/hvXrwVN3DSQj9xxJvUP43f3JxPYMJCbMDBg4X9/MW5+fpNHm4GRlAxlHyvjpiiye+eAAewqrmJd6CwaDxr7iaqaM6sd7WcX85/93iCa7xoMj+7Izv4K4yCAGRgQR6GfE2uygrsnO2ZomZo8fREofZ9KsJ78bx3tZxcRHWFj0o2FOd7OsYjSDUxoLd0MRmCQCSvYXXeCXaw/x+J1xjI7ryd8evY0wi4kVu4s4WdEAQPq0EVKDE8LTXd4T4avvbi5V/2fVjVHAU3SvgDsaJjzIn/Spw1l34DQzx8a6bP/FcyDcKdV+i+/FMQJzU5OkvQBg7r1J2B1tTBzahyXb88kpraOgvF66oy7Znk9CVDDvPzFGtuFv9AE0HK2weGseP//gAHNWH5IGzPzyeuqb7YDGQ7fFSJfKuEgLS6ePJNDki8EAZpNRUjC/mpBIfEQwkUEmlu8qpNpqI7OgUi4+n+aWy3cBXO1Jeh/xualJLvYM1fagH3N3dKa7hGNXk07piiH8arglegV5B2jPwOVpQoRRTd0WihdBnCs+ExCRiYsy8uQCIKgYocXZW53BQy99fFR6qcRFWnhr+ij8fH1kBODG7FKmjOqP0ceH/1h1gP9YdYDvJ0ZKA2sPsx+r95+muMrKT+8YQJ/QQM5UN/Hz7w3kT1OG80raEN7bW0zfMDPFFxrJPVdLSKAf8eFBjE+M5P87cIafjonl1j6hvHB/Erll9dgcbbz64BCeumsgf338dt54aCR3J0fx+rQRxEVaMPr4MOv9/Sz5f8eJDglwHreniGqrjfkPJPOb+24hI/cc8ZEW4iItUisTgjXU7MetfUKIi7Tw/PpswiwmFmXkYTL6yIROqiFMLGh6Gkv1UtFr2mKsxW5E1chVIaMGsIhnQP1ML5z0EZV6N8lFGXnSECgyBKqZKgXNMu+jw/J5WbqzgPSpw0mKDmHqmBhenzaSqWNiWDgphRH9Q52Gyc25zBgTS1Gllf1FFyiqsPLsmkNMHNqHULOJfmEWmu2tTBsdQ98wMwWVVhrtrSREBfP6tBHsLqzilbQh7MyvcD6jF7MiCixIS+G5exJl8FGYxQSaRnF1E8P69uCZ1Qd54v0vabQ5GNa3B7/ZcIQth8ukx4x+bKsaWqQL7Isbc1yCiMRciEVBL/j176barj6zpHpcd6GzC8XVWlBuakHe2Yl0N+gdTYjeuq56VagLwOLJw6i22jhWViezxqkGIeG18UV+BYUVVmoa7aRPHc6mw6Xkl9fLF8tgcF4nPMgZZLExu5TJI/vRu0cADs0Z6DM+MZKxCRHMGBOL3dFKk72N9/aewqCBpsGGr0pZlJFHXKSFhF5B/N+MUbwxbSQDwoJ4bVseBRUNbM0tJz7CzL7iagBu7dsDm6MNk9GHogorc9Z9xQeZp1i+6yRPrzrAku35LNycy+N3xqEBjTaNZnsrS3eeYP+pav7jgwPMWXOQ/9l2nDvjw/nxiH4unjsig97yXYUYfXxcPhfGwoSo4EvGP6+sTrq1qQJXuCHqOW810lIsumomR3GMoAaEC6j+M+GpIqI09xdd4Ni5Omn4E4uEqikunjxMfhcZ7C93Ic+vz5aLe2py74u7G6fhOL+8njCLSS4iG7NLXWgo8UyFmv1YmJbCCxuOMPfvh+lp9iMj9xyzxycw598SCQk0EhNu5m+P3c4raSn0uugdJMZ0WEyoDD4qqrBy7JxzUSk43yBdY0Wof3iQP+/MvI3Xp44g+2wtPx0Ti93uXMCyz9by7PgE7h8aLXcKag4WwaEv31VIanJvCius0v1U3SUJ33g9fSXGVKU19V4sHdEvV4rOCuersSu4aY2dnqzXl8uhdXSe+r0wWAkDnjAsioAa4Xkh8os8NS6eP2Tk8cSdA9jwVancIs/76LAUcsIgCkhj1W//cQTQmDl2ANuPldMrJMDJe2Yco09oIBgMmP18AWeAx9bccrnYLNycKwNEnnjvSxptzudk0Y+GsP7gGZ67J9GZIsDWip+PgcfvjCPU7MfRs7XSG6V/WCBhFhNmkzOB0/6iC7z52QmMPj4YnGwQDwyJ5u1dhdybHMXafacxGJyRoKFmP0kVgdNYvHRnAROH9uHu5KhLtGl3XihbDpexMbvUxUNIDSgBPBon2zOMuQvuUY2ZwgtJCLqZY2OlYFQTnQkvEqG1C08WcBrAxa7jfF0zoWYTs8cnSEOuyCvzvzvysfg7g8kWZeRxsqKBgb2CnUnK2jTCzH7MTU0iu6SGV7bkktQ7hF9NSJTeKOMTI9lfUiMF6ZRR/Xnp46M8NyGRYTGhpO84weiYUBZtO47Zz4dXHxxGqNmPJdvzWTZjlEwbIe5LLIQiaZkwcu8vuiC9Z5Zsz5epH4RhW+/ZNT4xkp35FcwcGyvHUP3tKfeR0NrFWKptd8Zwfa3Da+zUwZ1GfbmrdEc8urrFU/NkpA3rw/xNOZyva5beI2rO5PAgf95/YgxpI/vx5kMjmfW9BJeAlrM1Tt9rwSd+kV8hPR2EVj1z7ADe31uMxd/IlFH9WbjlKK0a+Pn68Lsf3CKLAPzjq7McP1/HF/kVzmyJLQ7pYRJucboi+jtlPicrGwizOAVLcWUDdU02nv/7YR75SxZ9w8wMCDfTPyyQMzXN2BxtUovcmF3KM98fhMXfiJ+v0z1xd2EVv75nMB8fKWVeahLvPX47oWY/Zv71S17c+PWYLd1ZQGV9M/P+cYT9RRfk2AIuudZVWkNw0irXLHz+3Wl0ndny5pXVkRAVfEmYuFhwkqJDmDUunoWbc6X9Y2xChNQq56YmERTgnItFGXlSixZ5TMR9PPPhQWmELL04jmIxELnmZ606wInyelmUo6jKSY3YHa0AvPrgEFKTe7MoI4/1B88QE2bhse/EAWBvbaO2ycabn51k5thYqq02GpodhJr9eG5CIr/beITskhpmjo3l7V2FTBnVj8G9ndSWSA+xv+iCpP1mjYvnZGUDCzfnUtXQIg30cZEWqhpaWJVVTHykxZkqoLKBiUP78PQHB3ly5T4yCyoltSLiKXbmV8ixE8Jb/O8pWEgk7tLTmu7mWnx+o+CmFeRweYmwPLWjf7jEb8HhCY1H5QbvHxrNn6eOINRscjlO8KPis/kbchgd11Ny75HBzkour08bwfJdhSzKyGPjwTO8vCWPhEgLQQHOZFj2Vmeult49AvjVhETqmuy02DWeHZ+An68P/7sjn+W7Cpk4tA9nqhuxOzRe2ZLHudomiqqsMk/H7O8n8OR3BzC0Xxjv7T1FdEiALCgxIMJCD7OJgREWEiKdOVRKqpsIMPrySloKoWaTjBycM2EQb//rJLPHJzg59a3OyML6Zjv1Ta38M6eMhKhgwiwm/jx1BAvSUpyRjRfH4aWJKQzv34O4SItLwM2ijDz2F10g/6KBT0Bw0ip/LQSPOndq0QP9wqtyrMJQ+vSqAy5CWEAY4oSgmzUuXhowhYFVUEXrDpymodkhx1hNITtjTCwx4U6BWdNoZ0CEmefuSZTXWJSRh6OtDYNBY17qLaw7cJqlOwv4beotDO3bg9njBxEUYKSowsr8TTmkJvemydZK8YUGnv8om6c/OCgTYrVpznQJsz88yNHSGv5j1QHqm+0EmIz8cesxahrt9Ar2Z92BMzLBm4hteGHjEZkHJyEqmDcfGikNlPMfSGb2+AQWZeTJsf3xiH6syipmYEQQMeFmWmnjZKWVJdvzSRvWR9qGBMWlxg+owULqe+YucZc4pj1DtIqr4UXyTeOmpVa6C/oHSL/VBy4R8Pot+5bDZTLfs6iio/rbqkEv+odO5TMfensP/cMt0qvl9IVGyuubiQkzYzYZOVVl5alx8dzat4cUro/fGSfzk5dUN2CzQ0KvIMwmX0l9vLr1OAMjzPxkVH/+mJGHv58Bm0MjpU8PGbpd02jnNxsO89Z0px/7/2w7zhsPjaCm0c4LG4/w5kMjqWm08/MPD7LoR0NYvf80TS12Qi5GDzbZHbz2k+EUVVhlgMvCSSnM35Ajq9UI/2mxdRb0BSC33cJArGaJVLfian511SAmFlA9TaOnUVQ/bjWHSEF5PXPWfsXKx2+n2mqTtAg4hfSnueUMiwmVVIoKcZ3ZHx4kMsif8vpmEi7mnfnthiM4Wlu5JboHfr5OvWvi0D6EBPrx1z1FvPnwKD7NLWfT4VJsjjbqmmxEBAcwe3wCYRangvD4nXHM+3s2kcHO/DkPDInm1W3HGRhuJtDfjzCzH3fGh/PGZwU42trw8/HhN6m3sP7gGUkBZZfUEBNu5tk1h0iMCmb2+IRL/NVFsNLTHx4ktqczJ/rEoX3YdLiUGWNimb8xh/hIC7+akOiSs0d4vwAuOWXg60A4T+kT1HdKff8EN64/19P72p356K8mPFEr3sjOK4A7flZv1NQLdFXjE8JDZD1MiAp22WILrlUVXIIzNZuMNNocnK1tYs2TzgRI/cMtskhDanJvXth4hNieTiEuNLpFGXks+9dJIi0mQgKd7nv2No1AP18GRgQzISmK7LO1pCb35uUtx/hHdimONo0T562sP3CGQJMvc+4exIbss7z646EUVTg1KntrG1obkjutb7ZLLjTSYpJJm4b3DyUk0I+iygY0NOZMGMy6A6flOL24KYenxsWzu7AKQNIQQsjOHOssRyfohF+sPsTg3sEuEaAz3s2SnwltTvUeUtEevVJR33LJ+fqXXc0wmD51ONVWmxToqpCfvymHYf1Cee6exEs0TKHF9+4RQGlNM72C/aWbZZ8eAZhNRhakpZBdUsOK3YW8sCmHQKMPSb1D+DS3nBc/PsrP74rnsxOVnKy0YvT1kQqBWKhbNSita2RwrxC+mxjJwAOniQgOYOLQPtQ329lfUsP/PTyKmkY7q7KcEbh3J0fJ3cv/bDvOwrQUWRQEcClcIZ5VgLa2NppszoIii7fmER8ZRFykhVU/GyPfi1NVVl6fNsKZO71Nc4kAVd8ndYfqyenA03zqk2+5s4u5O84TrmVO/aamVq4UnjxRPHFyeqpFcOWC+wPXLbaAEOJJ0SGkJvcm/7yTly650Ehrm0ZRhVUmzlK9DVL69CAk0A97axv/uyOfmkanX/fTdw2krL6Zx++Mw2AAPx8DTTYHp6oaeX9vMVNG9ee9vadosjm4J6kXc+5OYGj/UBxtbfgaDGw+UkZpbTNf5Ffwmw2HOXauDj9fH159cChBAUZnEYqMPPLL6xmfGMmFRjsJkRZe3pLHAym9WZVVTL/QQAb3CmF0XE+ZmhWgV7A/O/Mr5P3OGhfPi5tyXJKJ3RkfzvyNF9OVpqW4CIGk6BBW/WwMs8cnuGzR1TnTp171xJuqvKtKl6ntiMAdUZhj+a5C6RYonoOxCRGsfOx2Z+oAJcuk6ra4ePIw/vb4GP7woyGcq2/hhY1OW0BZnXOeqq02frcph7L6ZmZ/byBDLy4KGbnn+K97Elm97zRPjYtnRP8w/jRlODPGxEoKZ8aYWPqGBuJn8MXu0Pgiv4IKq43xiZG8sPEIL2/JY3xipCwsIozmgHxG+4UF8uKmr1391HzpVQ0tNDQ75Bz07hFIhdXGU+Pi+eDJO2SNVuErHxRglIqLwQDFlQ2yXTW1r9g9PX0xIZve68QT1EVXL7RVxUpAXzTbHa6W/3d3wSvIrxCehLb4Tv+/0O7UvCoiak9Eej7ylyw+zS2XgmLWuHgpTDJyz3FrdAgvTUzhlugQYsLMrMoqJikqiPmbnO5uiycPIzzIn6fuGojZZMRggBPl9fx1T5GkVppsbdRdLLA8eWQ/yuqb8fUx8Px9SdQ12Tld00jf0EDe2FnAGzsLuDU6mJLqJh4YGs07M2/jlbQhvPX5SaKC/PHxceZxGR3Xkymj+hNq9gMNfjE+gf0lNfz6nsHkltVjMflya98eAFj8jS4vlXC1LK1pxtrytVBIiAp2MfDmltbx5mcFRPUIcPqgb8xxm3Dq2TWHLgn60aOjl9OdP7J+wRYQmQpFxSM9xiZEyDkXhm0x16KfkcH+1DXZSenTg7n3JjntIkH+rDtwmoSoYN577Hbefng0eeUNzH/AmVLY5mgjbWQ/Vj5+O/cPjWbhpBS+yK9gzrqvKKqw0tDsYPmuk1TWtzBldD+KLzTwakYeYYF+3Nq3B/PuS8LoYyAk0M8lH7oQ1GIhE3nvk6JDqGpwLkC/Xud0j3xxYw7HymspuOgOe76uhbn3OhPDVVtt0ugr3pXFk4cxNiGCyGB/FqSlkNynh6QOxfXFdYWW39G8eZpDd8JZX8yiM5W+OmM/+zaFvJcjv8rQB3+4c4ESEK5cj67I4sT5BlY+drusoSmCRPYXXZA1PqsaWpj39yOgaZRUN9IryER0qJkpo/qzfNdJii808vRdA+kbZqauyc57e0+Rf76B9x67nZKqRjYdLiW3rI7Ynmb8fH2YPLIf6w+e4VBJNQEXKZTF2/Lw9QV/o5F/T4lm9b7T/HHSEKd/8cWAE5Fwad5HhzlaVuesA5pzjlcfHCJfZKc75GFWzxorPxNUESD57ppGO+sOnL4k4ZTq5ldUYZUJxcIsJhd/ZAHVrqCfD3duhvpjwL07or7+pirsVd7c3QuvHiPuT8x5ZLAzb/wzqw9KN9Nf3zOY+ZtyWDgxhaljYlzuq6C8XrqdqhSHeHZmjo1l1vcSmLPmENYWBw/dFsPirXlEBPvT2qZRXteMydeHD568g6IKq8wHDvDixhxOlNeT0CuYZTNGUVBez6KMPF798VA51p/mlvO7jUcYGGlB06CwspGX01LkcyHsJusOnMba4uDNh0e52Hj0O1WBOWsOcexcHR/+7A4A6dqoumrqnwlh9Oxs3nHhOeYu+vNy4cmdubvhiSP3CvIrRHu8mTsOXZ80S3DlqkATLyo4NcsFE1MINfvJog+vTx0hBdkzHx7klUlDABgd15NPc8v549Zj2B1thJlNnKtrwdGm0SPQSFxEEHZHK3+aMlzm1ABksNDO/Apmj0/g6NlaNh8po6HFQUGFlQdH9KG8roUZY2Kpa7JLw9pz9ySyfFehFKgvbsyhttHGuboW4iKcVWJMRh/8fH2k0UsYs4RvdVVDi0z0lFtaR0KvIMnrWlschFlMl1Ahwv/+te3HWTAxhfuHRrvMhSfh3Bn/Yb39Qsyb/jshVPTCXj1e3+7z67OxOdrk2Lnzh16bVUJG7jnpk51dUkNG7jkWTx7G/qIL0sd7yY58npuQKH3qxSLxyF+yePj2GN7bW8yHT94hk6EtmJjCit1FGAzIAK4fj+hHSKCfLJ0nipOA0798d2GV01bySS71La3cGh1MqNkk+19S1ciibXkMjAjivuQo3vmiiPSpw6WB26DBy5OGsGJ3EctmjAKQY6BG1qoGZWHMnj0+QdoaxEKnL+p8OQUk3D0jVyqE23vuuhteP/KrAP0Wz503gng49ZGC6vcqzyo4yYSoYJbvKqRvaCDgFOgAt0Y7fXnBGRKd0CuIt/91khcv0iqvbT9+ke7woa7FTu8Qf4L9fXn1R0N59cEhhJqd23qRC6am0U5lfTOvbs3jq9PVLN6ax7LPT4LBQJC/EX9fA58fr2B8YiS/XHuIkEA/Gm0OCi/mNzlf38LSnQUs3JyLn68Pj98Zj4/B6e1SVNmA7WIOkPmbcpg4tA9J0SGy+tGcNYeY99Fhlu8qdAaH9ArC0dbGqqxiaprsnL7QyJRR/S/hredMGERG7jl6Bfvz4qavfc3d0R/u5qm9l001fokQcTXEW5/vWlAGwh2yPYgITpPRx4VuUCFy6yyc5MzmKBbNgvJ6KcR35ldIYb6/6IK85/Agf16fNoLBvUPA4Ew9OzYhgtenORf+OweG86sJzpD6x74Txx+25PKLNYdkHvlZ4+JJnzaC2eMT+L9/OQ3mi7fm0dNiwtcAP71jALPHJ3CsvJanPzjIsJhQXkkbwrIZo0gb2Y/0qcNZsj2ft/91krn3JvHBk3cQavbjVJVV8ukiB7/4XySUSxvWR1KO6dNGOO0KF1MRi/FN33GCWePisbd+ncdIzIt+sXcH9TlwZwu5XCF+tZNxdQZejfwKoedR24s4S4oOkalZO9Oe6mo3ZVR/4iItUksUroki4lFNE5sQFUxBeb10CezXw8xrU4bJbapwh3thUw7+vgaMPj4XIyn9mXvfYEqqGrk7OYr9RReY+/dsnh0/iLSR/Xjyvf28+uAQ5m/IkRqZ2PoLD4eFm3NptDkw+viQd66Ogb2CefXBIcz76DAWf2dl+xc35qBpTtfH3204wtLpIxmbEEFmQaWkYURCMDUysz06StWi1RSx+nHtyrwCLhGXeo1ev6PSa5oC+q286h7Znnaoh+r/Lmi23204QlJ0iHQ3fHFjDoUVVv7jrnje+vwkP//eQNJG9uORdzPJK7cS2zNQzvNLHx/lRHkDQ/v1wN7aRlldM28+NBJwRowuSPva/XN8YiRbc8ulS2SfHgHMHj/IGfp/X5LMO/8fHxzA2uLA7O/L2w+PZunOAtk3kU5i9vgElu8qlGMq5l1fNs7dzlVPtbibN0+Rvt1BobjDNynEvRr5VYLeIu7JHUq4xonUrJ4MNaqACA/ylzk41h04zaKMPKkligRZS3cW0GhzsCqrmDlrDrF8VyFVDU53trhIC4Migwk0+bJwcy4F5fUsnjyMgvJ6J43yvYEM6hXML8YnUN/swO5o5ZVPcvndphw+zS1nVVYxYOCNzwrYePAMYWY/iiqsnKpy5nx5bftxZo6NZWd+hRSo4MyR/tw9iQzsFYzF5AwHnZuahMnoQ3ZJDSfK63G0tRFq9qN/uIWEqGAqLmr2s8bFs+7AacBJFak7mor6FhkFKMZKaGwiNFyMzZUansQ86qME1ZdWva7I++KO0lGjddWgJKHtC48M0bYqhITwfn59NkUVVh75SxbzPjrMnDWHiIu0kBQdwowxsSzfVcj8Dc6846ICVHNrG69syeODzFOkT3OmI65uslFQ4YwMDQnw483pI3nothhKa5qJtDiDt55ZfVCmBl44KYUZY2LZfKSMQ2dqWLG7iHn3JRFqNrF05wlaWttYuOUoOWdrCbOYWDtrLK+kDWFIn1DAWUS6ptHuQtvoxychKlgWfwYn1SJy16jjLOZa9XJSd8P68dPvljtj1LwcXAsuiV5BfoVQHxRPE6q6Q+lTeHrynBAP46KMPBkNKB5gIRQFjD7OvBVC6Iiq6OFBTn/khZNSaLQ5eGb1QVmXcXRMKO/tLaagooGd+RX89I5YQs0mAv2MDAy3sP7gGWfh3AeHYrM7WLTtOKnJTtdBkdGwp9mPjw6dZXxipAzNFn1eurMAi8mXiUP7yP+njOrPa9uP0yc0EKOPD0u251NQ4ay9WVBeT/5Fu4AqFNVqMQXl9fxi9SEZdq9CDYHXQ9Ae7oR7R9twMX9irty1oz9OXahVIaT+L1BttZF/sdqT+hzM35DD2qwSpr+7l4Lyelkx6tf3DJbZBsVCL+wlQQFGbosN47Xtx1myPZ8Xf5DMz747gGWfn+TFjTmkDokmKSqEW6J68Nw9iQQFOOup/mHLMfqEBhARHMBz9yTy5kMjJbUzZ81BXth4BHtrG69MTOHxO+PYmV/BxKF9OFfbzIBwCwmRIdKzKDzI6T46Y4zTBpLQy1l9aNa4eGeA10XffrU8ncwPf1E5WZlZzEs/vJWVmcUuAlpAv3sR86svB6c3VN9oVYFUeAX5FUA8SEJL7IygEEUCVH5UuFypgl2g2mqTwkxAcOpCGzMZfaSxVAg/k9GHT3PL+eXaQ2SX1GA2GRkYEcTouJ6kTx3O/pIafnpHLD4+TsPWm585E1I9fmccvr4GTlR8XUTXoRmYe+9gYsLNHDvn1LB+ueYQ5+tbiAzy572sYg6fqQGc2+aS6kZmjIllxphYluzIZ8qo/piMPsRFWnj/iTH87t+TefzOOB6/M44Wm0Z2SQ3LdxWyYGKKLECtaq9ifJbuLKBfz6+rGomx1ecYVxe5ivqWdrVBd4JZ/+KL4/S5ysV4q9q2qMGp+j2rC4GA4HvHJkTIAgxqjvKZY2NZtC0PW6szb0r6tBHMGhcvDdKiJJrqppma3Ju3/lXIUxd55Jc/ySW3rJ6FE1N482LB5TcfHsXCSSmyLFtNo51Geyv33BIlozWX7yokPMifYX17UFjZyI9H9KXoQgNv/eskL2xwhuVvOlzK0ukj+dtjt/Pqg0Nc+j46JpQXNh6hqqGFBWnORWvJ9nz5jC6clEJRhVVm9kyKDpG2g/Ag53jePzTapdiKux2s3sakN3aqu9tvm8O+2vAK8nbgyYgpIF5iffSfer7qsyrOEdtx8eIv3Jwr81HD19r4/qIL5JbVOSvhuNEmRKrW8YmR5JbVsb/oAhX1Tp56yqj+ZOSeI7GXs2jy/AeSWTbD6QIWZjExc2ws7+8txqAZaGhxEGAy8t7eU/z2H0c4VWVlQE+nQXXdgdMk9griu4mRLNmeT0yYmVczjnG8vIGZYwcQ6OdLYWUdTfY2GZoe29PMit1FrDtwmvSpw7l/aLQ05FZbbTz9wQGeXXvReNsnRBr0Rsf1lFXv1ZSsIn+1zdGGn49B5jkRL2hSdAgLJqaQPm2ES41HMd7uaA93wludM/2LL3Y4+iLbYrERx6dPG8HS6SNdXALFPOtzawuN0x2fPzYhgjcfGsktUT1YurOAqoYWl+x/n+aW88hfsqhqaJF92plfQfqU4aSN7AcGA022VpldU1A5wtf76VUHqGpwJhZ75nsDWfb5SRfPqY0Hz7Ds85M8/b2B7DlZRWOLxqmqRiKD/Qk1+5FbVkdJVaNsT8zJlsNlLNp6XCbuUoX0lFH9Sd9xgo0Hz/DsmoMcPlsrUyyoYyva0ufF0c+PmF/x252gvtE1cQFviL4HqAYWT+G74iVs70FRaxWqx4i2RdSmMNKpGiDAn6eOkKk+9X1bOClFUjXBAU43slCzH3lldS7FdAWEYenZNYd4/4kxLJ0+Uhos+4cFYjYZmZeaxKJteS6RlaLai8jV8seMPPx9YEx8OFtyyjD5GHkp7RZnVsA1hzD6+OBoa5P3JQxXQvta9rDTFW1sQoT0iQckty9SsgJy3MRLrmqhqvFQ+NqLcVINzwXl9S4GZtX4qE9n6+nFF1q++FzV1vWGSeFKpz5DauoFuDTqUMy5WPAWTkpxaukXjYQiz7y4j9kfHqT3xQLZ6rMm3CLn3jeY33+cw/938AwRF8fL2uJgyfZ86pvsnLc6a7+er2smNTWJMfHh0h20qMLK4m3H6R8WyODeIc7c4ncMICTQj9FxPalqaMHR1sZv/nGEQJOBW/uESnrN5mjj1j4hbo2R6w6clsWgn/l+ArtPVrF8VyFhFpNLfhVwjbYU+cfF+HdFMItnryOXU3Vur0d4NXIPULdtnoS4qrnptfeOjCuqkUw88KpmJ7aKcZEWSd/o+yb6NO2dTDYdLpW+2R88eYfUTlXBJoyjA8ItMlf23clR/HnqCHr3CMRk9OHu5Cg+/NkdLgbIualJsmrMrX17EGjyxa5BVmEVJyut9A8zc3dyFIDM73H6QhPVVhvPfHCAGe9mOTW1jDzpM6zei6CDhNYtfMf1mrUYI8GtCgjbg56HFgvXo3/bJ8dPb3z0xKeqc6l3bxOfiTlWjbF6Y6UaoSgq1HsydgutX5wvvFtMRh8Kyut55sODZBZUkhAVzMBeQZhNRrmbe3LlPqnJPr8+myXb8ympbiK/3Jkyttpqo9HmoNHeyvmGFn46JpY3PzvB0bJ65v39iPR0WpSRx4rdRTz9vYH0tDjdO2eNiyck0I/7h0ZLA/Pv7k/GEmDEx8eHe2+JYtG245TXNgHw6o+HygVHjPfs8QnyeY6PtLCvuFoupGKREnOhphnOK6vj2YvVszoSuPpdliib1xH1qfLr1yu87ocK9C9xRyu0Ozc0fcSYO+Gg17w8XVO0mzasj9Q49VGF+4su8MLGI7ySNkQWrNXzp6IPwj1QuPXNmTCIaqtNVqoXUDPZzf7wIEunj2T5rkIamh2YjM7gnj9kHCMu3Em/iDwjwh1ScNjCi0RkYxTnzxgTy0sfHyV96nDpdihoA6Gdib7p3dLcjWlH2HK4TAYNtTe3ete1joJE9By43ginT9Y0c2wsz3x4kIGRQZiMPrLajRrlKgqMPL3qAKeqrDJJVVVDCw+9s5fki37WYp5E8Ngzqw/y5kMjZXoAsbhMHukM+pn398M0NDu4JTqECbf04r2sYmLCzDTZW3nph7cSZjHx0PK9zEtNYuEnuRh9DTKTZUigH8+sPsgfJw2RbqaiCMXb/zrJqz8eyjMfHKDC2kJSVAgL0lJcnj2xAxK1WEUcgbgPsbh98OQdbmmmJ1fuw+JvvKRYhH7BdTdfV0sj/7Y4d6/7YQdQ+Ww9D9ceRy5+67V3daLdTbi7RD3640S79w+NlhFuoj+Cd31xUw5P3zVQ8tBCe5v+7l5mvJMpNQ0hxK0tDlbsLpKCcuZfvy5bVlBez/Prs1mU4UyilBAVTFJ0CGEWk4unTEy4mf97eBQWfyNP3TWQpTsLeOQvWazNKuHpDw7y8Dt7qbbapHZ1/9BoFk8exsJJKdLoKbwSMgsqZUDIysxiwoP8SRvWh4Wbc/n5hwdkMWB3nKg6d+3N68bsUpdjPL2A+p1OR0K8vXqRaqCQaDchKpgPn7yDZTNGSbdSEWYPzmCZOWu/oqC8XiaWEoItPMif1Rd3WmIHk77jhIwbGBgRJNPWiuNNRh9iws3M35hD/zAzf/jREIy+BinE56YmERHkz/JdhWSX1FDfYqe+2U6zrZW+oWZqGu28+PFRAP44aQgZued4etUBmVMm1OzH6QuNFFVYuWC1Ex8exGPfiZM1SEUd2qToEKmMiF2jeE4jg/1llKZap1RFmMXE/AeSL0k9LDyExD3rKS7V/tCe0PXEr3uCXj5cE9A07Rv/GTVqlHYt4lhprfbUe/u183XN2vm6Zk3TNO18XbP8rLNwd467v9trU/+daHPPiQrtqff2a8dKa7Xzdc3aJ9ml2u0vb9eOldbK487XNWs/SP9cG/jbf2qfZJdqx0prtUdXZGmTl+3WfvDnf2kjFmzV9pyo0M7XNWs/eWu3dqy0VjtWWqvd/vJ2bc+JCu2T7FJt0G//qa3ZW+wyJsdKa7U9Jyq0UQu2aXtOVGjTl2fK8z/JLtUeXZGlpb2xS1uzt1j21d0YP7oiS3t0RZb8Xu276Mcn2aXaT97aLfv56Iost+PV0fyoc9lZqNfrzByJPoh7E2O250SFnBsxb+IexfHiR3wnxkRtW4yXOFZcT8y9GPs9Jyrk9+frmrXpyzNlm4+uyNLW7C2WY/pJdqkce9Hvf//z57KvYk7W7C2W1xZzLto7VlqrTV+eKX+rz+aeExXa5GW7tdELt8nj1edBPEf659bde+Np3tVxV8fVU1vdiavVbkcA9mtuZKpXkOvg6aG5knbcPVTqQ6eHp+/E559kl7p8r3/51RdJLzSmL890EbTiJVZf3vN1zdq///lzKbD1L414eVWhLtr7yVu7tUdXZGmfZJfKl1j/MupfOnf3LwSR6Ft7grU9IX45L7NeIHd0vuiXuwVAjOvI33+9eIqxEgJaPd/d9cR4TV+eqY1euE2Oj2j/0RVZ2jufFWjDfp+hTV62W86PKjw/yS7VBv7mn9qt//2J9s5nBVriC5+4PEeifXGOujBNXrZbm7xst5b2xi4t7Y1dLguOuCd1kVEXMnUuxfMl7kksNOocqmPR2UVaXezUxeLbErZXE54EuZcj/4bgjkN1V5VE5dDV6DVxruAbhQeDyr8Knlmt4iKOEdv8FzfmYPE3kprcmyU78nnph7fy1z1FFJxv4MMn73CpRLS/6ILk0lWeUfX6EDytWoRXJNES4d0CehdAfRg2XJrBEHBJsqUPv3ZnV3BnrOwsp6mfm47OE/PlibuV3Pjqgy4Z/VQDuacxUa8hsPHgGX72vYEu3816bx+FFVYcWhuv/Xg4q7KKZeHsOWu/In3qcBKignly5T4wGLCYfJkxJlZmPFTnQFRUUpOawUVjeXkdRoMP81KT5LMjqjnZW9s4W9PE69NGsDKzWPLhIqxeX1wavk4zobdNqAWy3aVb8DRPauHy69kDpT14OfKrgK5wZHouXF/wQN+WyoerfJxw4xM+yJHBTou/Wuj39YuJj1ZmFkuOVviX+/n6kJrcm535FTx0W382Zpfy2HfiuOViX1S/d2GYUr1pRB/U6Mrn12cz76PDAJL3XZSRx8JJTt9u4Ues3qvqf633sxbcpyhGIBYp4JIkZHpbhtqGWoezs5ymfm5UgauiI7uJgJiTNx8a6bRJrPjykpqhapvqmIjPxNh8mlvOy1vy2HK4TM5RVUMLRh8f+vcMxOTjS6jZT3LuYxMiSJ86nKU7CwB4Z+ZtvPrgEGmnENkExfVUIS6SmonI4oWTUhjaN5R5qUkyadf9Q6N5/4kxPHePs3Tbr+8ZLAtTb8wuZXxipPQyElHHgPSyEakUVNuE6rElBLPqsSXGRNgh1GezI1fgGxleQX6Z6E6Dh96VUV8BXP9wqg+sSDhkbXEaBfPK6li+q5CX/5krXyShrQiPkde2H2d0TCjLPj/J6JhQNmY7Ex6JRUKNwBubECEj7ARUl7D0HSe4Mz6co2V1FJTXu0TZCc1TDdJRBax6X6qftTC4iusu31XosnCotRg9vbju3AA744Ukjnc3N+3Nl7u2xH2IORHVg9Ti2npvIXd5QoR3y7CYUHoEOkM/VJdOgNd+MpzVs+4gzGLiZGWDTIMcZjGRW1YnYxSEK6Qoam1tcVBQXs/Tqw7w7JpDpA3rI68pXAbFefMfSGZnfgVpw/qwZEe+dI9cmVlManJv/mfbcZ5edUAuvkt25MvizOq42hxtFF9olM+sp3dIeLqI/ET6sXc3/zejEAe8HPmV4HI5uI6MoZ2FahgU3KjgSwfM3awlz//kEl5W5SvT3tgl+WzVSCR4W5VXT1v6hQsHrxrSpi/PlNypp3vUG6bUe3DHoavniftSOfz2xra9cW7vPE/HtveZnst1dx/6H9VwqY6DarRWDcF6g/Ox0lrtJ2/t1n6Q/rmLoVNcUzwL4vgRv996CT89aekubdLSXU7ue+kX0nYyedlubch/b5FGTnd8veiX+F9w6e98VuDWiK03aKrGcdX47Wks1b57mo+OcKPw5XjgyL0a+RWgs5yru/Pa8x8HLtlOuoMIhImLtBAUYJQuWmkj+/HLuxPwM/oQZjFJ+kXQEyJY6J2ZtznDsS9SKKJvIkPiI3/JYv6GHCobWsg5UyNTAKTvOCHrOi7fVQg4g0D096CvlyhoGgGRI+XpVQdcxkrfTvq0EdLvviv+u53VxDs61tNn+t0FuFJTKvWk/m9ztLmEtYNrUFNeWR2/WH2ILYfLmLniSwDpzihy9dx7SxS5ZfUs33WSKaP6S61V3IegssKD/PlQ8c8WFEphhRWjjzN468yFRiYO7UNG7jnqmu002tpYva/EJT+NO+pPvf+GZgfL/nWS1OTePHvRL1zci0i5IGpvLtycK6tA6fOk6GkWMTbu3Ec7uxu+Jt0FuxvupHtXf4AVwHkgpzPH3ygaeUforNVdf8yeExVa4gufuHXfc9eGXiN7dEWWi2ugqg2LY1S486AQ7mRC+/739H9d4t2iadolGrb4TH9PQuvX90F1ZdPvCoS25s6zQb1//VjoNbiOxu9KoO+T/t719yCO9eS5I777yVu75THqLkkcc6y0Vluzt9ilLfV7dSemfi68UIb9PsPF80R4Q4kdmmhTPU/1gFLnSn1O1N/qTnDPiQqPXkydGWN349TRu+Xp/+tZO+dquh8CdwEjvYL8UrT3oLnbjgvohbin7b1KPei3++35xasvqeqeqGlO4SNeOpX6+CS7VBv5+60uL6pecOrb1zSnEBfubuIYvdudeo+eBLm7cdMLKv1YtDeGXaFe2oO7frhbQN31Q/1bFZQqNaIX5GJ+9O6lYqGdvjxTG/n7rdon2aVuXVP1tI7+2urYqn7meuEuKBIxt/rnTqXm9K6B+mur49GZufP0mbv5cPddVxb7awlXVZA722eAV5B3DV15YNvTSNQXTN+Ou/bUF00coxeuQiCIoA1Vm1P9jD0tIvprCSEujunIT7u9/renXbkbC09j6Kn9y4Envls/Fu4WV/GdKkiF4BNBWurxKsesLoZiLtbsLdbSln6hDft9hjbs9xlyN6Tfean3r7ajBidNX54pFwx9zMGoBdtc4hL0XL66GOvHQr0XMVZ6vryz6IqQV8f6etTMv3VBDswC9gP7Y2JivpGbvl7gSVt2d0x753n63935eoGiCg93C4Sn//UatV5IeKI6PAnqK3m53Gnp3dF2e5qf+O0u4EuvoY9euO0S2kGv/erHRR+cs+dEhTb8pa3apKW7LtFwj5XWSgpDaONpbzgNmp9kl0q6TJ1Ld7SWEOKPrsjSJi3dJRcDEbk7YsHWSzR7dwuDp2An/XipNJC7Mehobi5HKF+PQlzTrgFBrv7c6Bp5Rw+JJ81a07quLXRGILanjarf6TV1/TF6Ie9usdC/vB1FZHamn50dh/aoqvYWtfbgaT7cLZ763+60VH0/1Hn3dC1xnhDEQ/87Qxvy0pZLIiPF9SYv2y0F9ORlu7XhL23V7v3TTm3oSxlSuxZ2FNGGqtWrfLaIEFY9bcRi1NGz6u5ePY2Tft668h5cr0L5cuAV5N8QOhJGndGWuyLEL+dh70jou2tf1QwFPGna7jQ8T0LfHQfelXvp7OedzcHh7v498antCSV333vql0pRueOu1TQFqibsaR7VcRc0zIgFTmGu597Vc1TbiCrw9Zy6SoG0xzWrNhe9IuCu3+7GxdMx7Y3rjQyvIP8G0RWNvDPHtScI3Glv7X3fVa3Xk9FO73uub789A197/Wvv+Mvpv7v2LmeR7ew5XemXKmz1uUjE98IuoSalcnctVbMXv9WFUvDdnoynol01yZraL3fj0pEQFzEOqhB3twCpY6G/H/G3O+rqejZaXi6uttfKaqAMsANngCfaO/5GF+TdAXdbc3ff6x9u1cjmyXDk6SVsTzNSv9tzokIbdDGzYmd2GJ29X/G7K1pzd8OTkOmu/ui1d5Xm0I+hKuj1mrHek0QIS2EcVekPfRuqIBd/C3591IJt0qCtHqdq8Gp77e0+3LmcdrQ786SIuBPsnjT8GxmeBLk3adY1jI6KKHSUdMlTgI2onKIWqtAXQ1CPVUPixbGz3tvHHx8c2qnEUu3dm3pttTCH2u/2Ev93VDCgu0K2O9NWZ4oX6AtOuEueJcL74etSdyIvCiCLUNgcbTKnjkiiJgKMpr+zlzeVgiBBAUamjOovg79E+UBxLfHd+MRINh0ulQmu1GRo7gpYi+IQ6vyJ1Ar658bTOIn7V5NeAZeMgb4N0bebKSzfU9KsbqNWuvLj1ci7B6o21VV01jNGHOvOX1vdqnfUT/3vzlIYHe0sLjdPeXego+2/gCeXQ7UNd5+395leE9cbzNVUw2oOcX3+ek3TpCavuhGqdIyqiet/1HsUv8UOwxO91t646dts75nU38fNALz5yG88CIHakd+tJy66o3Pa+18YxDwZ6dTz3FFEnRX+mub5hW5PkHf1Gp2BOzqgI0pJvX/9caogbi+vSXufeVokhbuguuDqg3pU6DnsY6W12vCXMrThL12ap0X92x1doi4A+nFwd69dWYjdLR43E7yC/AaFJyGtfu/JO8ST8akznLCqdXXWDa2zi4l6/c705XLQFY3dXT+6shvyNO5CQ9Zz5OJ6etdNT3Mm+iB4bbXQhzueub2xVK8hgn3c7aT0z5W6OAkDrf6+PdkDVLTnqfJN7LKudXgF+beM7nj4rkRoedryt0dbdKXNy9GO2nsx9ULtaqCzQtyTd47er74r19W7HKrGRCGE9Zq0pl06Z4JiWLO3WBv0239qaW/s0qYvz3SJ/BTX1AtqdQzU78WP8Cd3V8lHvQ/9WKmukqLPendUd+gMXXIzC3FN8wrybxXdoUl0po2uCmNxTEeaWnf0zRM6emmvhaAQd+Oqell4EvYC7nzDVY1Z1VTV8nv6+pjq9T1p5CIISG/DUDVh1XVP9VFXFxZPQUz6cfBk61B3HO52B57Q3XTJjSb4vYL8KqGzgvVqa+Tutv5dCVW/HArjSu/vchany22nu+FOQ1fpEAGhZao5ulUDpfr73iWfaaMWbHPJPvjUe/ulEbIjjVa0r+ZDEQJb5aZV7V8v8DuzqLc37+r5k5ft1kYt2CZzm3dkz+nqrqYzx9xoVIxXkF8FdCQsvw3h0t7/4rOuCHhP53TX/V3uAtAd7VzpNd0do3p5CKj+1Cqtof7/SXapNui3/9T+d2veJQUm1MRZqjBUtV89LaNG5Kq7hz0nKmSuFPV7tU8qZaK/7/bsIfpnQlxPb0T1NHadpancKS3tHXsjwSvIrxK64yH6ph+2b0p4Xg7Vo2ndR7d0F9wJGZXXVo/Tp98V5+qDYtS/xTFCExe/BfS55vVVnwSPreaK119b/D952W4t5b+3uAh4dVcw8vdbtR+kfy4Tb7lLfNUZDtvdmHnyzlHPdberUdtt7zo3AzwJcm+FoCtEe8EI7QXxqP97ql5ytSqaXE4ARWcr5wjo76ujKi3icxGsJAJb3F3zcgrsXslYqvU/52/IIbOgkoff2ctDy/cyZ80hl4AeUavU5miTdTJFMWc1KCivrI45aw65tD86ridPrzrACxuPyHbzyupcCm3PGhfP8l2FFJTXy5qqotj2M6sPyrZFhZ2ZY2NlIW8Ae5vzpQ+zmFg8eRizxsUzNiGChZNSCLOYGNgriFCziQUTU1ixu0jeh1oJyV2AjzpWAmpgl6jz2tDsuU6np/dFX2RbPfZyn4cbDV5B/g3CnTDz9CB6EnzXS7kq/X21d5/6grpqxGl3wJ0g6Az08yTuISEqmA+evIM//GgI6dNGeCzZp1aJd1cW7ti5OlkkWcXce5OY/0CyjHQUZd4q6ltYvquQmkYbz645REF5PRX1LazMLKam0c7AiCAabQ4WZeRJAfjsxYr1z6/PpqC8HovJl8Qo59hWNbS4FDZO33GCBWkppE8bQVykhYKKBmaPTyA86NK5c1cMWV20n1+fLRcAMa/vPzGGZTNGAa7FpfWLtojkVAtYizFwh5tdiANeauWbxpUYdG60baR6P50pa6c/pyvHd9UbwtN19HlN9IZD8bfwHnFnQFRpDjUplTPXeIY2/PdbZepYfYUf0bbqnij68s5nBZISERDHqVGbKm+tcuPqGB0rdRZtVvl2d/eu9kmlUtS+qfesjq+4jjqO7mwxV/K8Xy69d60CL0d+Y+BafzC72h8hBLoSbn0512jvs/Y4W/VvPeeseoZ8kl0qU8C6+18VemqmQT0HLYSfXuDqA6QEny0WDyGo9VkpxYIxYsFWyb3rC4gcK611aUvTXAW7O35c8PTqPanHi8pCKtfuiR9vLwjoSuDOKHq9K0JeQX4DoisP5jfx8F7Ji/JNhlvrDXGdcYFUNVgRzKPWohTCVdNctXbxvz44RyxeQntW29D7dItzRFt6LVpkLdRrv6q7oQgUEn1RdxKqBi3aVT1b1DbVtt1lP1THTCx2+ut1ZZ668nlnjr2ehbimeY2dNyQ6a+jpyNB4JegM398ZdBcn3pl7VI2XVQ0tHfY5MtifORMGsXBzrvwBmP9AMosnD5PGwoSoYMB5LyIbIeBibBT9S4oO4bkJiazKKiazoJKnPzjI6JhQVmYWMzc1ifRpI5ibmiTPq2poIbOgkunv7pXce3iQPws357Jkez7xkRYSooLJLKiU9yIMldVWGxZ/IzZHG0UVVmf7O06wv+iC5O3Tp41wnQMNqq02F8OsavScm5rk0j/9+AmbQpjFJMdA5cxVeDL0643l7j7vCO76dSPCK8ivc3Tmwbxaln1PxttvC+76oxcEKuasOcQjf8miqqFzQsFk9GH+A8mkTxshBZ+434LyenntvLI65qz9isyCSuBrb5aqBqfxbs6aQ2QWVLJoax65pXUcPVtLbZOdNz4rYObYWJKiQ2R7j/wli7VZJUx/Zy+Lt+YxMCJIGkKFodTe2saCtBQKyut59G/75HVrmuz857qveHbNIWaMiaWuycazaw9RVGFl5thYXvr4KGnD+lxy/+FB/nz45B1ygQLIL6+n2mqT/y/KyGPh5lyeX5/tYuhUIVIgC4GvGm7bmzMxZmq6X9UbR/TBi6/hFeQ3Ca6GgO2uBaK7dgr6/qgCwN2Ckz5tBO8/McZFE/UkkBZl5DE3NUkKbzWPuBDcM8fGAk5tO33qcOk2KHJnp+84waxx8QAkRAXz5vSRzEtNYmd+BeYAH+LCLYRZTKzNKuGZDw9ib9NYMDGF9QfPEBNuwejjw3P3JFJUYeUnb2fy9AcHmDi0D2drmsguqSEhKpgFP7yVsQkRfJpbTl5ZHWdqmvj1PYMJNftR2WCjT48AVuwuIiEqmPSpw1mVVczD7zjdKPPK6uRYhQf5S8EZHuTPr+8ZzMrMYjl2iycPY/4DyVJI6wV6RX2LSz5y1Q2zvTlT50H9TOQ6V104r1ePrqsBb2GJmxzdWXzhcq/vrqCFp2M701d90Yr2inN01BchxG2ONuY/kOxCk6jH5pXVER7k7/Yz4S8+/4FkwOmWOHt8Akt3FnD8XD0L01IINfsBsGR7Pl+drqZvmJm+oYFMHNqH17Yf59f3DGb9wTM02ls5c6GR+hYHt/QO5m+Pj2HjwTO8ujWPpKgQztQ08pvUW3ht+3F6WkzM+TcnfQMwPjGS13eewGAw8H8Pj5JU0Ke55QyLCWVRRh4NzQ6p8c5c8SUv/fBWVmUVk1dWx9LpI+U5gLyvGWNiWXfgNLPGxbMys/iSwhldhToP6jgLuGu7K8/R9QxPhSW8gvwmxrXy8F+ukHV3/pXekxC+kcH+ZBZUsjKzWFa8EQIdcBHqqnau/j9/Qw4zx8ayZHs+JqOPFN42R5v8v6bRzroDp+Vnc1OT+CK/grc+P8nPvzeQt3cV8ut7BvPRoTPYW9sormrklUlDCDX7SaH6zAcHOH6ujl+MH8QbnxWQ0qcHM8bEsmJ3Ec/dk8iS7fk02hyEmk3UNNowGX0w+vgQFGAkNbk38zfl8OepIwg1+/HsmkNyl5JZUMnyXYXMGhfP/+7IZ0FaiqxSNGtcPEt3FlDTaON8fQsLJqbI6kNjEyIuezFV51QdS3VMPc3tt62UfBPwJMi91MpNjGslKu5KeH49x9rePXmKFhXtVNS3sCgjj+fXZ5NZUMmzaw6RNqwPSdEhJEWHSDrB5mhj4eZcyXlvOVzG8+uzefI9V+VkzoRBLkJ8+a5CAB6/Mw5rizNw5+1/nWTWuHjSp42QUaE78yuICHb+7hsaSH2zncIKK8/fl8Tc+5IINfsxNiFCctt+vj789v5kduZX0C80UGr+JysbePmfuTTaHJTWNDNjTCy9QgKYNW4gJqMPs8bFs/7gGeLCzazKKibMYpJCvKK+RS4UYRYTfr4+hAc5KZUpo/qzfFchs8cn0CskgNenjeD+odHMmTCI5bsKXagsld4S9Et786BCtOEpqMwdr36zwivIb3Jc7w+/O8Ht7p4yCyrdhv6rwgacUYWLJw8jISqYAeEW1h04TV5ZnUf+tbrRzu82HOHO+HByS2tltOX8DTkUVVg5WemMjkyICpYLwaqsYooqreSfr+fI2VoWZeTJcP6C8nqnllvXzMShfcBgYPG24/zHXU5u/TcbjvDTFV+yNquEmSu+ZH/RBWyONlbvK6HR5uBsbRNFFVZe+vgoPx0Ty7naZjAYiA03MzquJ3NTk+QOAKDgfD1Goy/21japbQtBXNXQwpRR/QkP8sdkdIqKqoYW5m/MwdrikPfkzjtHnROxowHYX3Sh3RQM7c2rOrfXe+Rzd8P4bXfACy86g/a21Z2hZVZmFvPSD291MbYJ6mThpBRmjo29pJ1lM0ZR1dDiQqkAGAzI0HWLyZf+Pc2kjezHrX17kBAVTFVDCzPHxrJ8VyExYWbCLCbZ9/Agf2aPT6CkqpHV+09z4nydFKKpyb1ZvDUPR5tG7x4BZOSe49UHh5BdUsOmw6WU1zfTpsGz4wcyLCaU9KnDWbI9n7pmO5X1LTx/XxKr95UwOq4nT343jt2FVTx/XxLv7y3Gz9dHFiueMqo/6w6cJsxiYlBUMJoGC9K+9kYBJ3Uyf0MOh05X8/7jY5gyqr808r7x0AgXrlyFcG1cOClFhtgL2kjkiUmfOrxT7qaeuHA1XYI7ntxdwecbHV6N3IvrAldCAwk/8I3ZpVIDVz1N9DlH1POSokOkX3f6tBHMfyAZP18fSZPMHp8gfaXDLCbmrDnE9Hf2smR7PlNG9Zea7MyxsewvusCcNYd4+sODvJpxjIdG92dQZDAWfydX/T/bjvPIHbH89v5biAhyJsgSQvyr0zX8ZfcpAvwgukcg09/dS02jnbzyesrqmvj59wayel8JxVWN0vhZWNHA6n0lHCur44LVKeSeXnWAFzflMGtcPEnRITz2nTjsrU7/cnAKYqFlP3dPIhaTkazCKuas+4q1WSVyUVRdKcWORXi7CA1ceLcI2kgIf0+LALhq1O58yfU0mnqOmGfVu+VmgdfYeY3jZjDgXC70L7T+O3d8OnztBVHV0CI1t7yyOskN6wWEuhOoqP/afzvMYpJuicJjJW1YH0LNftKoWXC+ntiIIAoq6mixa7w8MYWYcDMv/zOXULNJavqNNgfN9laKLzQSaDIyMMKCo1XjaFkdP/vuAD7cdxprSyuxPQMJCvDjzAUrv70/mT9kHKN3sD9Goy+nKhuIDgkgKMCP4+fqsbe18UraEN7POsXp6ibiwi0uQTwlVY38Ycsx6lsc+BjAz9dASp9QnrsnURosn1y5j7M1TTx8ewwffFnC69Oc2rgwBi/emofRx0cmwwKnN4vJ6COTX3VmvsQcCG3eUyKyznir3MjvjNdr5TrEteJVci1CbNsB6d+tftfeFtvTiy7aFMJOCGlACvmnVx2g4HwDrVobSb1D8PP1kRkQtxwuY/7GHBamOVPSAhc5bzsrdhdx58Bwss/WMmtcPM+sPsgraUMYHdeT/UUXeHbtIeLDzRh9fTCbjNLdLuNIGZ+fqMDmaKOu2UF1ow0D0NNiol+YmZpGGxgMFFU00GxvI8DkQ//QQEprm4kK9mfhpCEA/G7DEYIDTVhMvlQ1NHOiwgoaJPUO5qd3DODw2Ro++PI0AyPMVDfZefOhkVKYC/dEYUcQQnvOmkMcPluD0WBg9ayxkiMXY1httUn+XJ0T4RXkztvocmiRG1lw6+EV5NcpbqaHtD140rBFoI27NKvuPu/oGsI3Gpwh7gYDWPyNLJ48DHAKqSmj+rMqq1jSKiL8fOHmXGoabZTVNfPhz+4A4Dd/P0xhhZXokADON7SQ0CuIH4/ox/qDZwgKMMpFaG1WCR8dOsOvJiRSUtVITLiZJdvzyTtXh9XWSly4meILTfj5akSFmDlb3cjc+5zBRDWNNnLL6ukbGkBts4PYnoHYHW2cq28BzakBF1RYSYqy8Nh34nk1Iw9bq4Nf/dtg+oY5PVZyztZia21jyU+G8/a/TuLn68PCSSlUW23M/OuXJEeH8NRdA3lh4xE+/NkdJEWHSKPoc/ckyt2JGKf9RReYs+4r0qcM5/6h0XJO1PQGHWnfXXkWbhZ4EuReY+c1jpvxge1ssIcnoxc4NejL2cmkTxsh/xaGTqGVC84XIC7SIgNoDAanC6DN0cbs8YNYlVVMtdXGoow8jp+vxWjwJcDkyysXteM5677iv+5J5Na+PUjfcYKZY2NZf/AMJ87XM3/DEQoqG7GYfIgLD6JHoB9N9jZ+OLQPQf5G/vzpCUID/Zg0LIHNR8qYm5pESVUjL2zMwWLyxWLyxWwy4hfow+N3xrN6XwlN9lYC/CDA5EdG7jnmpToNoP/46ixnqpv47f23UNNo43RNI6FmP5ptrRTWN/Dixhx+NSGRP08dwaqsYkLNfgyMCCI8yF/megkKMEohLopGAKw7cJoFP7yVjdmljI7rKSNEwblAVlttLuH67QlnvU+5d5d6KbzGTi+uKXjK33I5L64njtzdNcV1hRug4M9VTTyvzFkI4vn12YRfNEaCU4jPHp+AyejDugOnmTEmlsVb88ivqMPuMDDttv74+fqwKquYuEgLC354K8s+P8nSnQWMT4xkyfZ8DAZ4dOwA/E1GYnsGkhgVjL21lXP1LUwd3Y83Pz/J6n0lADS0OHh710m+OlPLvL8fZtPhUiYOi6aH2cT5+hZ+NSGRGWNiycg9R7PdwZmaJkxGX74/KIK5qUmsP3iG4gtWiqqsNLQ4WL3/NABJUSHUNNopqLTSM9DJ3z+75hChZj+stlaW7izA3tom88CA010zKTqEWePiCQowuuRtuTs5ymXeqhpapI/7M6sPsnBzrjSUqpWWwLVwxfPrs6UPujBotvcstDfPNyq8gtyLawod+Q/r0VH1H08eD+r3QoDPHBtL+o4Tl/icL8rIw9riYP6GHJ5ZfZBqq42C8nqW7iyQibTCLCbmP5DMlFH9WbG7iMIKK4mRIcy7bzAbvirF3tomq/cA3BIdwvjESP6QcYy88jrK65p5/dMC8s7VUdNoY9a4gYQEmogNC+SRsQMYGGGmtKaJcIuJs7VWWhwaUSH+nLnQRFGllb8fKuU78eEk9+lBSVUjL318lNTk3pTWNmM0GPjuwAj+/GkBX+RX0GR3MDAyiP5hZhIiLTw0uj9nqpv41YRE4iItBJgMVFltzE1N4vVpIwizmDhzoZHxiZEUX2iUC5CYF+HJMmtcvLw/YehUUx3MXPGlTLz14c/uYP4DySzKyKOgvJ68sjq5CKjl/sQuSK0a1J5XSkfzfKMKcy+14sU1h460LXU77imjnoC6Ddf7iovj5kwYJAWQ4KxXPn67NMqJzIUARRVWVuwuYunOAqwtDkm7PPKXLPqGBlJS3UhMmJm4CAuv/ngoSdEh9A0zSyrmzvhwXvz4KD+/K543dhbgaGujX2gg5+ttJPYK4pcTEgk1+1HTaKfR5qCkuomMI2XUNjlocmicq2sGDE43xJAAQgP9aLa3YgDGxIczJj6cZ9cc4tf3DCYk0I+BkUF8b1AkSz8rwN8I6w+c4WSllWe+P5C/ZZ6iVdNYsaeIBpuTFkmKDmH+/beyaFseNY12VmUVkz5tBAvTUliVVUxCZBDjEyOZvymH1ftKeGfmbVJLBlz87VWIRGJi8RM7HXB6/yRFh0jKRl/uT0+/tMert6cI3Mh0jNfY6cV1g45czYRgFt4sQlhEBvtLLU8IaMF/q8eJgBnxt1gkqq02lu4scOnLbbFhvJdVzMCIIJbNGEVBeT0JUcHSNVHkJgGY8W4W/3XvYIbFhLJwcy4Th/Zh0+FSDp+tZeBFgf9FfgW7C6uYMqo/6f8vn8KKBgZHhTCsfw/W7DtNmwYRQSYmDe/D3/ac4uU0J9++el8JOWV1xIYFsuap7ziv904mBgzkn28g0ORLcnQI9jaN7w+KYF9xNbVNNnoEmhifGMnmI2Xynl798VCqrTZWZhaTFBXEZycqOV1l5ZE7Ysk+W3vRBuBMNZCa3JuM3HMu1FNpdSMRwQGXGDLFHG05XMa6A6flYqnnvgvK612SbnVm7m82vtzrteLFDQHh7y3gLqGSgF77FoJadVtUw8pFFCIgIxGX7iwgr6yOgb2CpGAuqrDyy7WHeP7ewewurJLRjDPHxrJo63H8fAzkn68nsVcwCyelMGfNQU5WNPLM9weyMvMUyx52uu8JQ2pNo51n1xxk7n1J/PnTEzTZW5k6uj97C6s4X99MfcvXWm5wgJEnvjOA6B6BvPjxURb88Fbqm+1sO1bOY9+Jo67Jzm83HCHAzweHow2j0YfXJg/nbHUj/7M9n/Qpw4mLtDDvo8MUVVnpFxqIn9GXufcNZvHWPE5faOI/7orn1W3HMfka+NHwvnz45Wle/dEQ7k6Okgvg4snDKCivly6KGw+e4ZUtefI4Mf4i8ZZIzrVwYgpTx8Rc4o5Y1dDCzBVfkj51uPRT18OT59LNIsTB67XixXUOob3pNT1VI/OUUEl/nLqtB6RAUV3nRGKqMIuJaqtNht4LLT05OoTvJkaSNrKfpBZ+ueYQJ883MC81CXtrm4zqDDD5YfTVWLHnFPbWVhlWX1rbzOKteWgamE1GggP8MPr4MPv7cazILKKuqZUB4WZ6BUN5fQv21lZaW9v4y+5CjD6+/PwuZ9Kr/PP1OFrb+MWag5h8nfc06aIA1uxtLN15gvP1Lfz8rnjiIi2EB/lT32zH0daGAQOnKhsoqWqkoMLKL8cncGvfHgwIC6SoqpHcsjqSo4NdhPiscfFUNbTw7JpDvD5tBP+7Ix9NQwrx59dns3jyMPLK6nh2zSH6hgay6XApiVFBZOSe4+7kKDlm6q5I7JbUBVlPm7ijUrzwauRefMvojEal17Y7ivQDLtlyu9Pk9cE/iycPk8E5Zj9f/m/GKEmpzBgTK9O0itwpwtCZFB3Cu5+fdGrjRgOJvZwh6HNTk+SxTbZWmuwOTlU18ouL6WwDTL7E9jRjNhm5LzmK3YVVnK9r5nf/nkxNo53j5+rYV1yNvbWNH4/ox4J/HqWtrY2oHmZCA535yx2tGhoas8cP4s3PTuDn68O00TEMiwnlqff3U3yhiYERZh66LYY3PzsJaEwe1Y93vzhFoMnArO8O5PMTFTS2ODh+3orZ5IPJ6MOA8CAcra288INk6Sv//PpsWTZu/gPJLNycy4wxsfzmH4fRgLWzxlJUYWXdgdOX0FX7iy7IIKmOoj09zeHNSKXo4U1j68U1h856EqjattDK1O8EhAcL4EKxePJ0aGh2epFUW22yvuW6A6eZe+9gUvr2kDlUaptsvLDxCOMTI1m+q5D/XPcVTbZWapts/Of/l83arBIWbzvOlNH9+MtPb8PR5swbvigjj/kbcmi0OQg0+RIS6EdCpIXUIdG8/8QY5v8gGbPJiL1N483PCrgzPpzS2maeXLWPuX/P5r2sYiYO7YOfrw9ltU1oQEsrnK5q5LYBYZy6YKWwsoGztU0AGH18aLS1sv7gGeb9/QjfTYjAgFOb35pbTq8Qf3qYTfzjUCk/++4Aws3+LN1ZQH2zA6OvD0H+vvQPDeSt6aOYe99gAv2MLNme75JIy+JvxN7qpHpmj09gY3Yps7+fQEqfHmSX1PCLNQeZMqo/gJyLgvJ65qz7iv1FFzr0RlIXZndxA+puTP252eEV5F58a+iKJ4FeK3PnXqb3YFHzWbu7TlCAUebWFty4tcXBzvwKqWnPfyCZHoEmYsLMbDpcSmpyb46fb6CwqoGC8nqOltbx3t5TxPQ0s3bfaUqqGjl9oYmZY2Ox+Bupb7JzpqaJySP7oWHgTE0TL27MoabRzv9sO47BAA+k9MbRprE1t5x59yWREBnC2zNG8/RdzkRYlQ0tpH9agMPR5jR6Bvuzbv8Z/j0l2mmA/F4Cq7KKOXG+nhPlDZyra+bwaWfIfe8Qf/qGBnJfchTn6po5XdXIf9wVz6d55zld04zRB8rrmjEYIG1YHy402qlptLN8V6GTejHAlFH9qWpoYcn2fGaPT6Cu0c68jw6zfFch4xOdHjEzxsQ6/dE1CDX7uVAnCVHBpE8ZLpOWqXMmFl+1zJy6ILt7DsRuas6aQ8xZc0j6mN/M6BaO3GAwpAJ/BnyBdzVNe7U72vXixsflBPl0xr3M3XGqthcZ7C+NlKICDoBgGlUjaPq0EZIfvjs5ijcC/Xj7Xyc5WdGArxFmjx/kNDL+4wj1zXasNgd/23uKn4zsx5qzNTjanFpys81Ok62Nuotuff9xVzy39u3B0x8coLVNo77ZxkeHzlBYUU9WYRVLPytA02Dabf1ptLVywWrDqGmU17fgA/zj0Gn8/XzoG2ZmxphYbI42ztU1U9PYwhPfHcAHX5ZQ12ynvL6FJZ8eZ9adA9mSU0bfMDPFFxrxAaJ6BOLnY+BkhZWc0noevv3r9AOiAtBvNhymX2ggx8sb+DSvnLzzDVhMBp787kDWHzyDtaUVgDCzH29czNGix/1DoyW1IuZCGJ1V/3NhgG5vgXdn57jZQ/uvmCM3GAy+QD5wD3AG2Ac8pGlarqdzvBy5F98kVKGhZuQTWlxBeT2/WH2I/7p3MBm556R7XGZBJXPWfkX61OHSO0NwvlUNLVRbbZRUNZKRe46GZgf2No13fjqa/UUXOFhygb/uPoXJzwdfHx9+Od4ZUp93rp4B4YHYWzVKqpuYe+9g1uwroehCIwFGAy/+ewoL/pmLyddAT4sJW6vG6eomDIDZZGDS8H588OVp/i0pggMlNYQGmqiob8bk68PMsQN4Y2cBGhAfbiYowI8HhkTzp/+XR4sd/H3B3mbg/cdvB5zZDxf8MwdNM4ABfjS8L//MKaNN01j0o2HERVp4cWMOmuasalTXZGf9wTMcLa2lT48AiqubZDbHsQkRbDlcJsPxVRuEsE248yyCS0vldVTSryOB3Fm7yfWIq8mR3w4UaJpWqGmaDVgDpHVDu154cUVQhYMaHSi+e359tvRd/q97B7NkR76siJNXVsfKzGKem5DIysxiKcQffmcvT686wMLNuSzZns9r24+Tmtwbe2sbT1305lixu4i/7jlFdGggs74bT0xYIEs/L6CmyU6zo41TF6xUWm1EBfuz9LMCztW30KeH0w2wvtmOzdHKD4ZE09PiT7jFhNnkQ6CfD/3DzBwtq8ffFz7Nq+Tuwb2otDbT4mgjKMCPjw+XYjb50jskgMKqRsrrmtl8pIzYMAsGwMfHh8FRQYAzJ3hIoB/NDo1GexuNtjb2FlYxIDyI/qFmfrPhMEUVViz+RiaP7McLG4/IKkRGo4EHhvYhMSqY1ftKSIgKJrOgkl+uPcSs9/aRWVApx13sbESUrFpQGXDZIbWXO0fMV3uRvGqqBX1Er7j29SzE20N3aOSTgVRN03528f9HgDGaps3WHTcLmAUQExMzqri4+Iqu64UX7UHVCN1l2QN4etUBF8+TtVklbDpc6lIcWRRfFgEsT67cJ32/R8f15NPccj46dIb9p6oJNPkyvH8os8cnMO/vh6UmnRQdgp+PgepGGyUXmugXFsjMO2JZ9q+T/HhEX9bsKwGDD098ZwB55Q2EW/xYt/80sT3NLH14FF/kV/DmZyfpFWzCaPSlqLKBRlsbBiA5OpjBvYPZcKiUNuDBEX3YerQcq81Jd1j8fXntx04aQkSMvrDhCDHhFvx8DFywtnC+voWeFhNna5p4Y9pI6prsvJqRR3KfECYO7UNG7jnO1zXjZ/R13oe1heLqJmLCAimpbuK9x26XGvnyXScprmrkwyfvkJGxWw6X8cLGI9zSO0TmWhHfqfPVXgItMZ9qkJf++856Nl3PuJoaucHNZ5esDpqmLdc0bbSmaaMjIyO74bJeeNEx9HyrEAhVDS3SzxucZd9e237cmd/7IhKigmV5NpELpKS6kZc/Ocazaw7yaW45S3bkc+8tUSRGWWi2tzI+MdLpe95kI9DPh1+MT+BPPxnGU3cNpKy2mTsTenK6uol/fHUWs58v6w+cpVdwAHa7g5WZxYyOCWXL0XNEBPlTXN3E+5mnWPavkzzz/YGcr2/B2mznuX9LZEC4meBAXwb3DmZTdhlGA/TpEcCOY+ex2lrpHxZIv9AAXvxBMusOnJZpBVbsLnKOhabRaG8lwGRk8Y+HMS/1Fkx+Bs5WN7JoWx7zUpOYOLQPS3bkk5rcm1CzCT8fA5NH9iPM4s/cewfz8qQhDO8XKiv+jI7ridHHh5hwi4sm/uKmHGLCzMwen8DCzbk88pcsl+RaqhYt/hbJtFT3RH3+FhV6zyb9dzc6usPYeQbor/zfDyjthna98OKyIDQwNdGSHuFB/qRPG0FBeb2syblgYooMIReoamjhxY05FFZYWZiWIvOMz/v7ERnBuGhbHq+kDeHNz06w7F8n6RtmJj48iIYWB+/vLWb3ySoevzOOmWNj+dueUwT4GvjOwHDe+eIUA8LNGIDmVogKNLIzv4KwQD8qG2z8cGg0H355mkB/A33DzIQE+nHqQhNLduTh6+PLxGF9+ODL0xgBG1BZ30yvkAAamh1UNrRgs7fx0aEzPPadOFbsLmLi0D68n3WKc7VNRIcEcrqmiSZbK+n/z2nobbFpLPn0OAZ8WLG7kAuNdh6+PYad+RVMHNqH1ftKeHVrHs0OO/nl9cRFBjH3vsEuY2Uy+mDCNQXw+0+MAZw7ExFYpfr06+kU4e0iPIlE4Y6O+PHLEdg3irbeHRr5PmCQwWCIMxgMJmAasKkb2vXCiy5D1e7U6E93mh3Aysxi6fc8Oq4ns8bFO7X4zbk8veoA8/5+BE2D/7p3MC99fBRAFl0uKK9n9f7TONraiIu08MIPkokJM7NidxGOtjYqG5wFkZtsrTz94UFW7T3FPclRODSNfaeq+d39SUQG+RMUaMJkgECjLzPGxFJltdGGRmGFlRfuT+K/f+BMWBUU4Ed0iD+pKX1o02D/qQsAtAFGA9ja4HxdM/5GAzFhgfQJDeDeW6JYuvMER8tqWfBJLqerm4juEYCvrwGDAfyNUHKhkdKaJky+0L+HmbhwM+frbTw1Lp6VmacYnxjJom15+Pn6MPOOWAKMfvQO8aewsp6X/5kruev0HSeYPT5B5nS3OdqkN4rqx696BAmtWxWmIn2wSA3sbm67+1m53nHFglzTNAcwG9gKHAPWaZp29Erb9cKL9uDp5XPnhqjPjqh+N3NsLOsOOPNx7y+6wJy1zsAVcNbRLK5swN6mcXdyFOlTh7sIoSXb8ymsrKd/qNlZSGKr0y+80ebAbDLSN8zMsJhQ6lvsaECTA7bklGP0BXtrG99NjMRk9OG22FBsGhw/30Bdk53fpN7C7+5PprjKyv938AyLt+ZRWd/MibI6yupa+PuhUqy2VkYP6Elsz0AC/X3pGxaIyQC+vj60ODTqmh2crmnmlS15HCurp8nWBmj8NvUWggNM+Pn60LdHAH3DLNjsbUwc1gej0Uigycgz3x9Ech9n1sb6i1z7Lb1DePzOOFbvO80z3xvInx8aSUyohXO1zXIhnDNhkCzMnL7jhDMv++RhLgWZhd+3modc9QNXC2CvzCxmbmpSuy6ll/ucXG571yq6JSBI07RPNE1L1DRtoKZpr3RHm1544QntBQWBa/CQ0BTdHSvyaM9NTWL+A8msynJ6qWzMLmX2+AR6hQQwL/UW/HwMMiBG8Ovp00awcFIK8RHB+Pn6sCgjj5wzNTTZHJTVNfPjEf04V9NEdkkNZbXNPDiiDwagb2gAUcGBnK1totrq5OP3naomwGhAA1765xFe2JTDss8L6BUSQEV9C4/cEUt1ox2bBkEmA74GiAoysfrL01Q0NNM72J+qxhZagV7B/iRHh9C7RwAP396fQJMPAX7wy7sTSOzl9FRptDuF87m6FuytbfTrGcim7FJa21ppsreyKquYGWNiiYu0kBQVxOr9zmIZoWY/XvrhrbzzRRFFFVYiQ/z5+fcGsiqrmOnv7AWQSbBmjo3lpY+POhfHNYdYuDlXZoacNS6e9B0nJBUjhLU+D7lqZBZw51bY1edExY0gxMGba8WLaxzucnGIz/UvteonrK8Pqfoyq3U+Vb/wh9/ZK6M5w4P8KSivZ8n2fE5WNvBK2hB++4/D/OFHQ9mYXXpJetvZ4xMoqWqUyaXCg/x5etUBmeI2zGLix2/tRtM0Wlo14sItrJ41lk9zy1l/8AyTR/bj95tz+dNPhvFFQQUffnma5Ohg7rkline+OEmjTcMHMPgYmP19Z2BPQaUVowFuie7B9xMjeXdPIWgGHrqtP2sPnCbS4k95fQttmvN6xRca0YBmWyt/mDSEv+4uuhjc44umteHj44MG9A72p6bRTnSPQJrsDooqGwk0+dJsd54XEujHugOnmTKqP7/bcISXJw1hVVaxLBQByOLLS3cWuGSUtLY4eGfmbS5zqU+zIIT3/A05zBwb6za1bWfzrtwoHLiAN/uhF9cdPAXywKWCXZ+HQxjLTEYfWbAAcElhC8jj0qeN4IOLLnPiOHH+03cNJNTsBwYDcZEW5kwYxMLNueSX17NgYgqhZj+W7izgaFktMeFmEqKC2V90AcNFf66xCRFkFlQyqFcwGAzcFhvKRwfP8kHmKd78/CQBRmculUZ7K8fP1bH5SBkBfvDTOwbwx63HMBh8+NGIKAorG8k/V0N0j0DKG1pIG9aHjV+VUtNk5/29xTw0OoYVu0+xYvcp/HzgVHMjvYL9abC10mxvBTT69zBTWu/MzfLYnXH85h9H+NW/DWJrbjl3Dgzn3T2FXLDanYbZzFPYWzUCTQZ6h/hztqaZhZ8cZVCvYMwmI6FmP9o0Z/3SGWNiCQ/6ugiHSJcASM+f/UUXeHFTjlzo3AUHqUbQORMGuS0cop/v9tBZIe5OMbieFgCvRu7FNQ1PGnlnzlGhCg2RRxucGqDIfKh/kasaWmTu8UG9gvDzddIAYxMiyCuro9pqY/muQqwtDu69JYo3PztJbLgZgKOldZiMBl6bPJy6Jjt/3HqMfj3MGH0NnKyoJzwogLomO09/byAbss9id7RxurqZuAgzhRX1GI1Gfnf/LSzfdZJzdc6gn8e+M4C/fHGKQVFBlFxoxOTrQ5Pdgb/Rl6hgf8Is/jTZWrG3tmLAQN+eAXyeX0VkkAmr3UF8RDCvPjiE9zNPsXbfaQZHh2DQ4LUpw5i/IYf88nr6hQXy0zsGsDO/gvGJkSzemsfz9yXx3t5T5JXVE3CxUMVz9yQCsHhrHrPGDZRj9LfHx8jFVPVcEYJ7fGIkU8fEyDF2N6/qnHR17j09Dx1p7ap2fy1nWfRmP/TiuoQnv2EBd9y30LrdRQuKPNrCqCY8JAQdoyJ9xwlGx/Vk4cQUQs0mHG3OYsRbDpeRvuMECVHBzBoXT/75epZ+VsAz3x9ImMXE3NQkXr5YhOLXH2Xzm38cweZoQ0Pj+4mRNNraKK9rpk9oAACnLuYChzaa7a3Y2wz0NPvxh4xjnKpqZNLwvvj7+bIrv5I2oNHWis3exr/d0gtHqzOX+bmL4/DCv99CoMnIiYoG/l9eJbRpVDTY6BMcyFPj4vkiv4IPvjyNn9EHPx8DPczOdLiP3xmHZnAqdRm550gb1oe7k6P44Mk7GBYTSq+QAP7woyEM7x/Kc/ck8r878nn6gwMUVVmJi7Tw/L2DOVPdREF5vRTiCzfnuvDhM8fG8tr243Kc3bmGqrspUQjb3Tx3Fp3lyTvK03OtwyvIvbhu0RX3MfWlHKAErKjeEmrBZXBu7asaWtiZX8Hs8QlEBgewYGKKzEte1dDC2IQI/jhpKIN6BbO7sEpWFYoJN+Pj40PvYH8C/A1EhwRwprqJFZlF9AsLpMXRRrOtlVe35qFpGr8Yn0BiVAghgX68kpZCvzAzU0b1I8DPwKbsUjStjcmj+rHoR0Mwm3zxNxnIOHqONpxpahtbWrlzYDg1jXbemXkbv0lNwtcAAyLMzLtvMMGBfvx2wxH+/Gk+g3tZeOmBW3ln5m3MfyCZ+RtyWLG7iPgIZ2DPlFH9eXFTDk+vOkC11Ub6jhPMTU3i7uQo5j+QTEJUMJoGyx4exVvTndWOtuaWY7U5ePmfTrfNFzfmkFtaS5jFJP3CwywmEqOCXYKF9PMn3ENFuTh3YfddeT4ul4K5noQ4eDlyL64xdIWbdPeSusuMp7a9KCMPk9FHRhYKLnz2+ARZoUZo9cJIJ4ylogRZXKRFcuSvTxvBxuxSnrsnUVYTyi+vp6bRjq8PBJiMJEaGYPE38ut7k/jrniLuvSWKDV+V8sz4BJbuPIHJ6MNn+RXYW9s4U91ETLiZyoYW/rq7in49zbS2tlFa28wft+bxi+8nUFDRQK8gJ/dtNkGvIH8cbRpLPyvA0QaLfjSEtJH9WH/gDKX1TWw7Vs5z9ySSVVjFyr3F3JUYyaKteQyLCaXaauNkZQPRIQH89I4BvLAph7omO69PG8HSnQUs3VnA+MRIpwvhmkOYjD6kJvfmZGUDAMt3FQJOjR7iWJXlTL0xY0wsb+8qlIZkm6PNSa88kCw18fb4b/3cXo7b4bVKj1wNeDVyL64ZXI7m5eklVUO+RduqtqcWS7A5nJRJtdUmEyzpA1JUTV14trz/xBipcS7Zns/8DTks31XI69NGMDquJ29NH0VooJ8z38vFz+ytbfxxSx5FF6y8/a+ThJpNTBsdQ0FFgzSOllQ1UlrTSHRoIOX1jZTWNtMvLJCkqGC2HyuntQ0qGlp44jsDuDW6BxZ/I022Vh77zgBS+gSz6XApBeX1hAf7MzAiCE1zGnXf/OwkQSZfVnxxCkebRlGFlZWZxfx0TCxldc0ABPgZWLTNOTazxydQVd/CK1vy+CDzFODU1l/bfpzokAASooJZPHkYs8bF89LHR4mLtJA+bYR05TxdZZWRs/B1tKeYC+Fe2Jm57aowvh7pkSuBV5B7cc2gO18+NcteXlmdDDqJDPaXW/uqhhbp2vb6tBGMTYhw4dJF1OfCzblMf3cvc9YccvFNzy6pYeaKLymqsJJ/vp5Gm0OWd3t+fTY1jXbga60V4Pn7khjSP5RBkU7j6YwxsazZX0JDSytj48OJj7Swel8JTXaNqoZmDPgQ4OdLkL+Rn94xgNZWDV/gse8MYF9xNY/fGUeo2cQjd8Sy4atSJg3rCyCLQCz/6W0snJTCU3cNJDEqiPAgfwZEmFn04FDWHTjN+MRI3t9bTK8gExm553hnxm28+dBIlmzPZ+nOAoID/fjZdwfwXlYxjTYHcZGWi546JgrK64kM9mdsQgQrH79dCmWR/uCDJ+8gzGKSi6c+olMIdfWz7sTNIsTBK8i9uMbgzl+8K1Cry4iFQS9AhGaeFB0ivxepasUxizLySBvWh3UHTjN7fAIf/uwOWWAifccJ0ob14bXtx3nph7cSF2kBTaO0pplqq42Fm3OpabTxwoYjzBgTK10d56w5xNKdBbz64BBe/fFQ7G0a6TuOM2vcQGJ7BvLRobNomtM1ct59g4mLCGJwVDADws2cqmrkD1tyOVvbRP9wM1+druWrMzX8dU8R52qb+NveU/Q0+/HW5ye5LTaMgvMNLNmeT0F5PQs35/LCxiO02FtxtGqcqmwEnCH0mw6X0j/cQnhQgPTICbOYKKxoYMaYWOytbXx1upaYMKc3zvwNObz9r5M02hzM/vCgjNAUvt8iUlNgxrtZ7C+6QPqOEwAukZqApLguZzemztfNDq8g9+KaRVdfbne8q+BbhX+zmodFQAh8QEZu2hxt/HVPEQ3NDpbvKpRRmKL90XE9GRBuIdTs50yB+9R3WD3rDhKigjEZfXj+viRiepr5654i5m/Iccn2Fx7kT7XVxonzdRw/b+XVjGNUWluYe28SFn8j/7sjnzc+K+B0TSPP35fEj4b3pcXeyi/GD6JPaCA1TTbuHBhOY0srg3oFUXKhiajgAB6/M57+4RZW7CmiT2gAjTYHS3c6y7A9fddASqqbmHBLL0IC/Qg1+5E+bQTp00bwzk9Hkz5thItGnRQdQqjZj5LqRrnTMJuc9ToLKhqYNW4g/cMtko4S1JMaqRke5E98pIV1B05Ln3JhwIwM/rpCk5jfruzG1CyJN0q+lCuBV5B7cc3CE9XiqaiAON4T77ooI89FyLe3UMx/IBmLv5Hn7klk1rh45qz9iqqGFhde197axjOrD7I2q8RF6xf5yi3+RmyONk5WNpBdUkP6tBHMHp8AOOmW1348nCe/O4AgfyONLW3UN9tJnzaCBWkp9AsNJD7cWQTi7V2FDI4O4da+PSivd4bkb8kpQwM2fHWWgZFmAv18eXVrHg+k9Mbo68M9t0RRWtNMTaON3204wrZj5SycmEJeeQN/+NEQGZEKSDe/zIJKMgsqiQx2GiXHJkTw9F0DOVfbTJjFRPq0ETx0WwwNLa2crW6kpMrK0p0FzBwbK10MxU5HzN+bD4+Sn4ncNsLYKXZE8HWhic5AP9c3ExfuCV5B7sV1BXfCV5/xsD2oAleviQNSSwwPcmqMKzOLncWDpw4HnBqlqn1GWkz8blMOj67IYvq7e3ly5T7m/f0Iv1x7iBljYnnqroHMvTeJ3208wsaDZ5j94UH2F13A5mjj7X+d5O8HzzJ7/CDiI8y8vauQqoYWsktqOFfbjMnoQ02jnfefGMPfHnOWZ+vbI5CQQJO8h+gegfz3D1OYm5qEpmnszK/g6bsG8l5WMbHhZmaPH8TPvzcQi7+RmHAzcyYMItTsx9GyWpkH5ZG/ZLE2q4RHVmTx0xVfsuVwGYsy8sgsqOT//lVIdI9AWQji7uQobu0TQtrIfnz4pJNuGpsQwcyxsdKoCbj4ios5ySurY87ar8gsqHSZr67YRtzN9c0uxMHrfujFNQx3LmSeXA47EgT69LXq55kFlTIARdUS1b/VnCqCXvHz9eHPD42kqMLK6LieFJTXs3xXocwzAvDo3/ax4Ie3EmAy8o+vzuJo03j7XyeZm5rEku359L9IzwT4+fLypCFUW228+PFRFvzwVkIC/Ziz7iv+9qgzN8nTHx4ETWNe6i38dXcRPkB5fTNLdxYwe3wCa2aNldGmIRfrdf72H0doaLHz6HcG8MzqgwyMCMLe2kZrGzI/iuj/++Fmjp6tZXRcT1ZlORewhWnOHO0i4RVAaKCfHB8xT8t3FcoxrGpoYca7Waz62RiX3VFSdIg0igpXTnUeOoOO5vp6C63vLng1ci+uWXh6ad29qJ15efXJmcTvX6w+hLXF4eJF4UnDD7OYpIHUZPSh2mpjY7azjsrYhAiZtjUhKpiEqGD+9uhtxISbSYpy5if5xfgEiqqslFQ5DY5+PgZe/mcuuWX1lFQ1MjYhgr89ehtTx8QwOq4nf3v0NsYmRFBttdGnRwAzxw5g/cEzlNY1E2jyYfGDTjfJOWu/ku6Ew/r24FRVI//76Qn+8KMhTBndn48OniUmzMxz9yRiMEBSVLAsu/biphzmrDlETaOd/9mez8aDZzAZfdhfdIGN2aWkJvfmmdUHmbPmkMxYqBop9UE8AIN7B7vsfsSxKu3iCR3x3e4iQsV5Nytf7s214sVNBxHFKbTDzIJKWa4MvhYU+vBw4QethvSryaGE58bz67NpaHZgMjrdC1/6+Cgv/fBWVmUVY21xcPhMLUGBviRFhbDgYih/xpEy8sobZBpY+Do/zP6iC/x6/Vc029vQNBgUFYTRx4DF38ivJiTKpFxLdxYw/4FkMo6U8cbOAgb1svDYd+KZ948jDO4VxH9PvJUwi4np7+xl7n3OSE01NUF4kD8bD57hnS+KePK7cby9q1BWTWpodsgFTBSsFsnDRCEJddzcjV97ATqq8O0okKe9YJ8bXSP3lGvFK8i9uGbQmeRG3fWS6tOlqkY3VUAIYa1y6foSclUNLS4Lg0iha21xEGYxMWtcPGMTImQOEkG7iEjQJdvzOVVl5df3DGbT4VLp+SHwk7czaWh2EB9hJsDPF4BQs4mJQ/uwaFseH/7sDqqtNp5dc4hJw/vw7henmH57f0prm5k1Ll4mrlqZWczMsbG88kkupbXN3NI7RLpULsrIo6HZQVCAkdTk3mTknpPCG7gkK6TQ5h/5S5ZMW+AuwEc/vu4yDOqzXIoxbS9Y6HrPVni58CbN8uKaRkfb4s5umzu7rdanS1WNbmpbqjujyrOL/oi20qcOlwtDUnQIs8cnyARaItMiIA2CS3cWMH9DDs+sPoi91VkvNCP3HDZHG6nJvVm4OZdFGXlUW20YDBoDIy28+fAoZo8fxPn6FiYO7cP6g2dwtLXJvN9PjYtn/YGzBJp8yC9vIDW5Nyszi3n1x0MZmxBB2rA+LN9VSI9AE6+kDXHxi09N7k1QgJFZ4+LZmV/B3NQknrsnkUUZebLPkcH+zBoXD3ztoqjmnhHUlD53iruiyHqj5dzUJBchrs97o4entm5WeAW5F9cEOjJidcageTl+58+vz74kwlAVMKo7o6hco+9PRb0zClREkGYWVEqjp5qcS3ir/O+OfKwtDp67J5FX0oYQZjERF2mRQnLx1jzsrW1MGdWfhKhg+oeaqbQ6vVk2ZpdKoQ+QFOXsW26pM495Qq8g/jR5OPbWNl7bfpy0YX0kffTiphymjOrP/AeSWXfgtMxQmDasD0t25Mudg6B3RPUkIWCFUVMdP9VHvKHZ4eKrr86dCjGO6vgJ98X5G3Kc11YiRdXruUNXI4JvRIHvpVa8uKHQ1S22eKk72qYLXj196nAXjwuVogFn9KaAyOkyNzWJ+RtyyD5Tw8KJKaw/eIbcc3Uk9w6RWrAQkEKYA8xZ+xXpU4ezdGcBlfXNVFntLExL4f6h0eSV1cmEVKIakb1N49UHh0jPlSmj+rPuwGnmpiZJ7d7ib3SG7u8qZNa4eH6x+hCrfvZ1lXuxuKmLEDgXN5W/F94+oh3hUbN61thLXDzFGOnHUd2puOPW9fN0uUmw9Hz99ZxMyxO1gqZp3/jPqFGjNC+8uFo4X9d8VY7fc6JCe3RFlvboiiztfF2ztudEhXb7y9u1Y6W1sh3xc6y0Vjtf1yyPFcdrmqZ9kl2qJfz2n9on2aXy3D0nKrQ1e4tl+8dKa7U9JyrkedOXZ2qfZJdqj67I0j7JLtWeem+/dqy0Vnvqvf3anhMV2p4TFdqoBdu0NXuLtVELtslzRVtqO4+uyJJ9Eb/dHSPaF3156r39cqyOldZqt7+8XV5n+vJM+be47uRluy8ZI3FNta3unif9OfprXU471wqA/ZobmerVyL24odAVjasz3hSezgGn4W/WuHjp8aJqrcIoCu7zx+wvusDouJ6yjZ9/eABrSyuvTx1BXKSFRRl5WFsc+Pn6yJJz8x9IZt5Hhzlb0ySTfGUWVPL0Bwf5w4+GEGr2kxWLFqSlSI1d5IYRBsmiCivrDpxm1rh4aQB9ds0h+oYGcvpCI0unj5S7DqF1A5J6EVA1bf1YFpTX8+yaQ7z/xNfavn4MvimPE7Wf1zu8xk4vbgp0Nqxf9ZRwV9jX3TmifZEdUUAYPUWNSZGrRRyvtiN4dMFRAyREBbPmybG899jtjI7rSVJ0CLPGxWPxNzJjTCxBAUaZPTDMYmLBxBTpBQNQ12Rn3j8OA87I1F9NcBopxf2lDevDSx8fZebYWMDpN36+zhlINGfCIBKignn/iTG8+uOhDOwVJIW44P7npiZJoa/ei/DQUcdFjOXYhAhev5i/xZ0QdTc/3WGwdDfPaj6XGxVeQe7FDYeuCgl9oJA+GZM74bAoI08KN+HVkhQdIjVykcdcvbZwZZw1Ll4GDolkXknRIYRZTPLaKzOLmTUuno3ZpcxNTZLCcG5qEusOnJZh7glRwSydPpLEXsEs3VnAws25krcW3PiqrGJe+uGtJEQFS08Ts+nroG5hYATw8/1aJKjZI9X7FPflrqqS+r1e8Kvjp/+8qwZLd3A3z93R7vUAL7XixU0BvcHLnWFNCALhD+2JehHavCqE9ecDbmmH0TGh7C+pkdr7zLGx0qgpaI6EqGBpxBTti2uKUnLC11x8J44HXAJ2ABZuzsXmaCMowCiFu/AFVw2TT686ICkcVYvWC0aVvlL754kqUQ3KorAy4DZlwpXiRvcn9wYEeeEF/3979xcqV3HHAfz7rX+o4EOhXqhYSQuKKFIjhJKLT0oeYl/E0hQrFB9sfbBCAxURRLH45oPkpQiBFoVWRexflBIMGAQJ1bRNStJtaGiRXuKfq9IYXyIxPx/uznXu3Jlz5uzdc2Zn9/uBJe7es+f8zk387uycmTntfei5fbepkI8Fldv2yH8/wt4Xj2Lf97fj9m9duWFCkRsi6NYscS69+Evrfe3uVmtuRElsMo0bUvjArddsCHM3esb/gHL95y6Q/ck97pz82atu29jMzaaZlv4kIrcvV790oyAXGdvKhbacGYV+C3T17Ln1AH7yezfh1HtnN/RvP/qH4+ut8HCIn9/KDvvaw5mlbru9L/wdo3c/Xp/t6e6A5L8PwIaA9lv1fuvaBfQ9y9uwfM0VjRcNY994HPfhlrr4K/l0sVNkrGsfuuvT9beLjT/39++/7t9swYW4u0DqulY+/OTcprXU/Ukyfji6fvT7f/1X/PjZt/DEy/9cP+6+u27Gcz/aGe3X9mt3a7P7yxT4Hxruz727rl2f7OTf1T78/YSt8/CiqPt2UiLE5/1CJwCNIxcx2zy22D13Y6L98eCxsck5+06NZXZjuN3rbt+p941On7HR6TO2/fEDduNjf7Y9T7+xYZx2zjndvf9wtJ6m/cTOPTVOe1bGanf9u5p1SIwjV5DLwosFXhhW4TaxwGs7hptck/pZGNzhccMPFTd5x59gEwv/2PHcPsJzCifvxPYTq6vpfHL1FbbzEuJmCnKRqFTotAVhblCFLe9YYMeOF/sm4PYRC1q/tRzOnMwJY/daOEs19btp+6CbJMTbak69b5EoyGVhTLMlmPpZboinpofnBFfYlTM6fWZDuMf40+rdPlKt71QXiX+8tvMPP3C6yvndNL13nrpNcijIZSFM82u9C6mu3Sht+3Wvdwkut73fIk99CMS6Y8LXwrAP3xcGfds5ThriqWOoRR6XCnKNWpG5MslMvqZRK5+ev7Bpmduu9bhjhMfzhTXH1uJ+6KVj6+uUx2agun37+/HXUPdfcyNkwnXBHTdLNRz2mDrHSUajNP1d5e5PQxnHYune90Mtcpk1OS3npu1iXIs31rptao3HLjr6tcQuiqb2lVN327eRnGsIqeeL1mLuG/pokZPcQ/IEyQskN6+RK1KJppZd0xjpFLcOyeFTH2y4y1DseGGr1L/bfFhHrPUbu9mFr8taM6GvXr55n+H+wudN3xakJ7F0z30AuB7AdQAOAdiR+z61yKUGTRcr295n9sVa36k+5En687teEAzf1+XnXVrxYV2x/vdFuzDZB/TRIjezkZmd3PKnicgMirVwc9Y491cw9KfiT7Lin9+aDfuz2+407//ZdoxUfSlt3wrct4m2bwuxmqW7wS52kryP5BGSR1ZXV4c6rAiAbiERrmmSw7846YLMv+lwqsuj6WKiC1i3ZK2bxt/lwyS1FK/Pr28aYdq09kxbzQrzybQGOcmDJI9HHnd0OZCZ7TezHWa2Y2lpafKKRTrqEhJdA8Vfl9sFrhNryfst5YdeOrahPznkr3Vyz/I27Dv476w63fvch0nshsix93T9PeXI3eeirBvem1h/S9cH1EcuM26Sfuic7Vy/b9gn3La9P767acan/zx39mRqck/uOeVsM83+ecmHPu/ZSfIQgAfNLGttWi1jK/Oi640MUsu9hkvHdlkvvek4ud0aXY817zdwmFW9LGNL8k6SKwCWAbxC8sBW9idSm65hlrpwmnNRsEvXh/+h4N4bk9rnVoYsyvB0YwmRinS9I3zqTkbhNltp/ctwdGMJkcqtnu1+R/imUTP+Nl1el9mjIBcpqGso5w4/jL1X5peCXOZOLWORJxk7nTuGfNq/g1p+p4tKQS5zZdpB1nU/fbSwu+hjn5qsM/sU5DJXphlkk0wOmnYLexLT3qcm68w+jVoRabCVceIi06ZRKyIT2Mo4cZGhKMhFRCqnIBcRqZyCXESkcgpyEZHKKchFRCqnIBfpkSbRyBAU5CI90YxIGYqCXKTBVkJYMyJlKApykYRptKgV4jIEBblIglrUUgsFuUgDhbjUQEEuIlI5BbmISOUU5CIilVOQi4hUTkEuIlI5BbmISOUU5CIilStyz06SqwDeHvzA/boCwAeliyhE576YFvXcS573NjNbCl8sEuTziOSR2E1RF4HOXee+SGbxvNW1IiJSOQW5iEjlFOTTs790AQXp3BfTop77zJ23+shFRCqnFrmISOUU5CIilVOQTwnJPSRPkLxAcqaGJvWF5G6SJ0meIvlw6XqGRPJXJN8nebx0LUMieTXJ10iOxv/ef1q6pqGQ/DLJN0keG5/7z0vX5CjIp+c4gO8CeL10IUMgeRGAXwC4HcANAH5A8oayVQ3qGQC7SxdRwHkAPzOz6wHsBPCTBfp7PwfgNjO7CcB2ALtJ7ixb0hoF+ZSY2cjMTpauY0DfBnDKzP5jZp8CeAHAHYVrGoyZvQ7go9J1DM3M3jGzv43/+yyAEYCrylY1DFvzyfjpJePHTIwWUZDLpK4C8D/v+QoW5H9oWUPyGwBuBvCXwqUMhuRFJI8CeB/Aq2Y2E+d+cekCakLyIICvRX70iJn9ceh6CmPktZlonUj/SF4O4LcA9prZx6XrGYqZfQZgO8mvAPg9yRvNrPh1EgV5B2a2q3QNM2QFwNXe868DOF2oFhkQyUuwFuK/MbPfla6nBDP7P8lDWLtOUjzI1bUik3oLwLUkv0nyUgB3AfhT4ZqkZyQJ4JcARmb2VOl6hkRyadwSB8nLAOwC8K+iRY0pyKeE5J0kVwAsA3iF5IHSNfXJzM4DeADAAaxd8HrRzE6UrWo4JJ8HcBjAdSRXSN5buqaB3ALghwBuI3l0/PhO6aIGciWA10j+A2sNmVfN7OXCNQHQFH0RkeqpRS4iUjkFuYhI5RTkIiKVU5CLiFROQS4iUjkFuYhI5RTkIiKV+xxMxJ9x33IV8wAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.scatter(X[:, 0], X[:, 1], s=0.1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 数据处理\n",
    "\n",
    "\n",
    "数据以数轴(0,0)为中心"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "X = StandardScaler().fit_transform(X)\n",
    "plt.scatter(X[:, 0], X[:, 1], s=0.1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 创建模型\n",
    "\n",
    "\n",
    "以及查看各种评价"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Estimated number of clusters: 1\n",
      "Estimated number of noise points: 6\n",
      "Homogeneity: 0.000\n",
      "Completeness: 0.004\n",
      "V-measure: 0.000\n",
      "Adjusted Rand Index: 0.000\n",
      "Adjusted Mutual Information: -0.000\n",
      "Silhouette Coefficient: 0.376\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "from sklearn import metrics\n",
    "from sklearn.cluster import DBSCAN\n",
    "\n",
    "db = DBSCAN(eps=0.3, min_samples=10).fit(X)\n",
    "labels = db.labels_\n",
    "\n",
    "# Number of clusters in labels, ignoring noise if present.\n",
    "n_clusters_ = len(set(labels)) - (1 if -1 in labels else 0)\n",
    "n_noise_ = list(labels).count(-1)\n",
    "\n",
    "print(\"Estimated number of clusters: %d\" % n_clusters_)\n",
    "print(\"Estimated number of noise points: %d\" % n_noise_)\n",
    "print(f\"Homogeneity: {metrics.homogeneity_score(labels_true, labels):.3f}\")\n",
    "print(f\"Completeness: {metrics.completeness_score(labels_true, labels):.3f}\")\n",
    "print(f\"V-measure: {metrics.v_measure_score(labels_true, labels):.3f}\")\n",
    "print(f\"Adjusted Rand Index: {metrics.adjusted_rand_score(labels_true, labels):.3f}\")\n",
    "print(\n",
    "    \"Adjusted Mutual Information:\"\n",
    "    f\" {metrics.adjusted_mutual_info_score(labels_true, labels):.3f}\"\n",
    ")\n",
    "print(f\"Silhouette Coefficient: {metrics.silhouette_score(X, labels):.3f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 查找最佳值\n",
    "\n",
    "\n",
    "先用比较大的数值，然后用比较小的数值微调\n",
    "\n",
    "eps设置的值为0.1, 0.5, 1.0, 1.5\n",
    "\n",
    "\n",
    "min_sample设置的值为10, 100, 1000, 10000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 0  0 -1 ...  0  0  0] 2 571\n",
      "[-1 -1 -1 ...  0 -1 -1] 1 8446\n",
      "[-1 -1 -1 ... -1 -1 -1] 0 10000\n",
      "[-1 -1 -1 ... -1 -1 -1] 0 10000\n",
      "[0 0 0 ... 0 0 0] 1 0\n",
      "[0 0 0 ... 0 0 0] 1 3\n",
      "[ 0  0 -1 ...  2  1  1] 3 881\n",
      "[-1 -1 -1 ... -1 -1 -1] 0 10000\n",
      "[0 0 0 ... 0 0 0] 1 0\n",
      "[0 0 0 ... 0 0 0] 1 0\n",
      "[0 0 0 ... 0 0 0] 1 0\n",
      "[-1 -1 -1 ... -1 -1 -1] 0 10000\n",
      "[0 0 0 ... 0 0 0] 1 0\n",
      "[0 0 0 ... 0 0 0] 1 0\n",
      "[0 0 0 ... 0 0 0] 1 0\n",
      "[-1 -1 -1 ... -1 -1 -1] 0 10000\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[[{'labels': array([ 0,  0, -1, ...,  0,  0,  0], dtype=int64),\n",
       "   'clusters': 2,\n",
       "   'noise': 571},\n",
       "  {'labels': array([-1, -1, -1, ...,  0, -1, -1], dtype=int64),\n",
       "   'clusters': 1,\n",
       "   'noise': 8446},\n",
       "  {'labels': array([-1, -1, -1, ..., -1, -1, -1], dtype=int64),\n",
       "   'clusters': 0,\n",
       "   'noise': 10000},\n",
       "  {'labels': array([-1, -1, -1, ..., -1, -1, -1], dtype=int64),\n",
       "   'clusters': 0,\n",
       "   'noise': 10000}],\n",
       " [{'labels': array([0, 0, 0, ..., 0, 0, 0], dtype=int64),\n",
       "   'clusters': 1,\n",
       "   'noise': 0},\n",
       "  {'labels': array([0, 0, 0, ..., 0, 0, 0], dtype=int64),\n",
       "   'clusters': 1,\n",
       "   'noise': 3},\n",
       "  {'labels': array([ 0,  0, -1, ...,  2,  1,  1], dtype=int64),\n",
       "   'clusters': 3,\n",
       "   'noise': 881},\n",
       "  {'labels': array([-1, -1, -1, ..., -1, -1, -1], dtype=int64),\n",
       "   'clusters': 0,\n",
       "   'noise': 10000}],\n",
       " [{'labels': array([0, 0, 0, ..., 0, 0, 0], dtype=int64),\n",
       "   'clusters': 1,\n",
       "   'noise': 0},\n",
       "  {'labels': array([0, 0, 0, ..., 0, 0, 0], dtype=int64),\n",
       "   'clusters': 1,\n",
       "   'noise': 0},\n",
       "  {'labels': array([0, 0, 0, ..., 0, 0, 0], dtype=int64),\n",
       "   'clusters': 1,\n",
       "   'noise': 0},\n",
       "  {'labels': array([-1, -1, -1, ..., -1, -1, -1], dtype=int64),\n",
       "   'clusters': 0,\n",
       "   'noise': 10000}],\n",
       " [{'labels': array([0, 0, 0, ..., 0, 0, 0], dtype=int64),\n",
       "   'clusters': 1,\n",
       "   'noise': 0},\n",
       "  {'labels': array([0, 0, 0, ..., 0, 0, 0], dtype=int64),\n",
       "   'clusters': 1,\n",
       "   'noise': 0},\n",
       "  {'labels': array([0, 0, 0, ..., 0, 0, 0], dtype=int64),\n",
       "   'clusters': 1,\n",
       "   'noise': 0},\n",
       "  {'labels': array([-1, -1, -1, ..., -1, -1, -1], dtype=int64),\n",
       "   'clusters': 0,\n",
       "   'noise': 10000}]]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eps_list = [0.1, 0.5, 1.0, 1.5]\n",
    "min_samples_list = [10, 100, 1000, 10000]\n",
    "\n",
    "# params = np.zeros((len(eps_list), len(min_samples_list), 3))\n",
    "params = []\n",
    "\n",
    "for row, eps in enumerate(eps_list):\n",
    "  params_row = []\n",
    "  for col, min_samples in enumerate(min_samples_list):\n",
    "    db = DBSCAN(eps=eps, min_samples=min_samples).fit(X)\n",
    "    labels = db.labels_\n",
    "    n_clusters_ = len(set(labels)) - (1 if -1 in labels else 0)\n",
    "    n_noise_ = list(labels).count(-1)\n",
    "    params_row.append({\n",
    "      \"labels\": labels,\n",
    "      \"clusters\": n_clusters_,\n",
    "      \"noise\": n_noise_\n",
    "    })\n",
    "    print(labels, n_clusters_, n_noise_)\n",
    "  params.append(params_row)\n",
    "    \n",
    "params"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 热力图\n",
    "\n",
    "\n",
    "因为eps和min_samples两个参数决定模型的好坏，所以需要同时对比，用三维的图形来显示\n",
    "\n",
    "\n",
    "首先看数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[2., 1., 0., 0.],\n",
       "       [1., 1., 3., 0.],\n",
       "       [1., 1., 1., 0.],\n",
       "       [1., 1., 1., 0.]])"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clusters = np.zeros(((len(eps_list), len(min_samples_list))))\n",
    "\n",
    "\n",
    "for row, eps in enumerate(eps_list):\n",
    "  for col, min_samples in enumerate(min_samples_list):\n",
    "    cluster = params[row][col][\"clusters\"]\n",
    "    clusters[row, col] = cluster\n",
    "\n",
    "clusters"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 图形\n",
    "\n",
    "\n",
    "分类"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.xticks(np.arange(len(min_samples_list)), labels=min_samples_list)\n",
    "plt.yticks(np.arange(len(eps_list)), labels=eps_list)    \n",
    "plt.title(\"Clusters\")\n",
    "\n",
    "for row in range(len(eps_list)):\n",
    "  for col in range(len(min_samples_list)):\n",
    "    text = plt.text(col, row, clusters[row, col], ha=\"center\", va=\"center\", color=\"w\")\n",
    "\n",
    "plt.imshow(clusters)\n",
    "plt.colorbar()\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "噪点"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[5.710e+02, 8.446e+03, 1.000e+04, 1.000e+04],\n",
       "       [0.000e+00, 3.000e+00, 8.810e+02, 1.000e+04],\n",
       "       [0.000e+00, 0.000e+00, 0.000e+00, 1.000e+04],\n",
       "       [0.000e+00, 0.000e+00, 0.000e+00, 1.000e+04]])"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "noises = np.zeros(((len(eps_list), len(min_samples_list))))\n",
    "\n",
    "\n",
    "for row, eps in enumerate(eps_list):\n",
    "  for col, min_samples in enumerate(min_samples_list):\n",
    "    noise = params[row][col][\"noise\"]\n",
    "    noises[row, col] = noise\n",
    "\n",
    "noises"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.xticks(np.arange(len(min_samples_list)), labels=min_samples_list)\n",
    "plt.yticks(np.arange(len(eps_list)), labels=eps_list)    \n",
    "plt.title(\"Noises\")\n",
    "\n",
    "for row in range(len(eps_list)):\n",
    "  for col in range(len(min_samples_list)):\n",
    "    text = plt.text(col, row, noises[row, col], ha=\"center\", va=\"center\", color=\"w\")\n",
    "\n",
    "plt.imshow(noises)\n",
    "plt.colorbar()\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "轮廓"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.03770721, 0.04149896,        nan,        nan],\n",
       "       [       nan, 0.41866311, 0.50607465,        nan],\n",
       "       [       nan,        nan,        nan,        nan],\n",
       "       [       nan,        nan,        nan,        nan]])"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "silhouettes = np.zeros(((len(eps_list), len(min_samples_list))))\n",
    "\n",
    "\n",
    "for row, eps in enumerate(eps_list):\n",
    "  for col, min_samples in enumerate(min_samples_list):\n",
    "    try:\n",
    "      silhouettes[row, col] = metrics.silhouette_score(X, params[row][col][\"labels\"])\n",
    "    except Exception as err:\n",
    "      silhouettes[row, col] = None\n",
    "silhouettes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.xticks(np.arange(len(min_samples_list)), labels=min_samples_list)\n",
    "plt.yticks(np.arange(len(eps_list)), labels=eps_list)    \n",
    "plt.title(\"Noises\")\n",
    "\n",
    "for row in range(len(eps_list)):\n",
    "  for col in range(len(min_samples_list)):\n",
    "    value = \"%.5f\" % silhouettes[row, col]\n",
    "    text = plt.text(col, row, value, ha=\"center\", va=\"center\", color=\"w\")\n",
    "\n",
    "plt.imshow(silhouettes)\n",
    "plt.colorbar()\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 分类图\n",
    "\n",
    "\n",
    "- eps: 0.5\n",
    "- min_sample: 1000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "db = DBSCAN(eps=0.5, min_samples=1000).fit(X)\n",
    "labels = db.labels_\n",
    "n_clusters_ = len(set(labels)) - (1 if -1 in labels else 0)\n",
    "n_noise_ = list(labels).count(-1)\n",
    "\n",
    "unique_labels = set(labels)\n",
    "core_samples_mask = np.zeros_like(labels, dtype=bool)\n",
    "core_samples_mask[db.core_sample_indices_] = True\n",
    "\n",
    "colors = [plt.cm.Spectral(each) for each in np.linspace(0, 1, len(unique_labels))]\n",
    "for k, col in zip(unique_labels, colors):\n",
    "    if k == -1:\n",
    "        # Black used for noise.\n",
    "        col = [0, 0, 0, 1]\n",
    "\n",
    "    class_member_mask = labels == k\n",
    "\n",
    "    xy = X[class_member_mask & core_samples_mask]\n",
    "    plt.plot(\n",
    "        xy[:, 0],\n",
    "        xy[:, 1],\n",
    "        \"o\",\n",
    "        markerfacecolor=tuple(col),\n",
    "        # markeredgecolor=\"k\",\n",
    "        markersize=2,\n",
    "    )\n",
    "\n",
    "    xy = X[class_member_mask & ~core_samples_mask]\n",
    "    plt.plot(\n",
    "        xy[:, 0],\n",
    "        xy[:, 1],\n",
    "        \"o\",\n",
    "        markerfacecolor=tuple(col),\n",
    "        # markeredgecolor=\"k\",\n",
    "        markersize=2,\n",
    "    )\n",
    "\n",
    "plt.title(f\"Estimated number of clusters: {n_clusters_}\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 继续调整\n",
    "\n",
    "\n",
    "再细微调整找到更好的eps和min_sample\n",
    "\n",
    "\n",
    "之前找到的最好的eps=0.5，min_sample=1000\n",
    "\n",
    "\n",
    "现在在这个附近继续调整\n",
    "\n",
    "\n",
    "eps试一下0.3, 0.4, 0.5, 0.6, 0.7\n",
    "\n",
    "\n",
    "min_sample试一下800, 900, 1000, 1100, 1200"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[-1 -1 -1 ...  0 -1 -1] 1 7409\n",
      "[-1 -1 -1 ...  0 -1 -1] 1 8057\n",
      "[-1 -1 -1 ... -1 -1 -1] 0 10000\n",
      "[-1 -1 -1 ... -1 -1 -1] 0 10000\n",
      "[-1 -1 -1 ... -1 -1 -1] 0 10000\n",
      "[-1  1 -1 ...  0 -1  2] 3 2262\n",
      "[-1  1 -1 ...  0 -1 -1] 2 3965\n",
      "[-1  1 -1 ...  0 -1 -1] 2 4609\n",
      "[-1 -1 -1 ...  0 -1 -1] 1 6292\n",
      "[-1 -1 -1 ...  0 -1 -1] 1 6520\n",
      "[ 0  0 -1 ...  1  1  1] 2 423\n",
      "[ 0  0 -1 ...  2  1  1] 3 625\n",
      "[ 0  0 -1 ...  2  1  1] 3 881\n",
      "[ 1  1 -1 ...  0 -1  2] 3 1290\n",
      "[ 1  1 -1 ...  0 -1 -1] 2 3096\n",
      "[0 0 0 ... 1 1 1] 2 64\n",
      "[0 0 0 ... 1 1 1] 2 105\n",
      "[ 0  0 -1 ...  1  1  1] 2 146\n",
      "[ 0  0 -1 ...  1  1  1] 2 215\n",
      "[ 0  0 -1 ...  1  1  1] 2 310\n",
      "[0 0 0 ... 0 0 0] 1 13\n",
      "[0 0 0 ... 0 0 0] 1 19\n",
      "[0 0 0 ... 0 0 0] 1 24\n",
      "[0 0 0 ... 1 1 1] 2 32\n",
      "[0 0 0 ... 1 1 1] 2 45\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[[{'labels': array([-1, -1, -1, ...,  0, -1, -1], dtype=int64),\n",
       "   'clusters': 1,\n",
       "   'noise': 7409},\n",
       "  {'labels': array([-1, -1, -1, ...,  0, -1, -1], dtype=int64),\n",
       "   'clusters': 1,\n",
       "   'noise': 8057},\n",
       "  {'labels': array([-1, -1, -1, ..., -1, -1, -1], dtype=int64),\n",
       "   'clusters': 0,\n",
       "   'noise': 10000},\n",
       "  {'labels': array([-1, -1, -1, ..., -1, -1, -1], dtype=int64),\n",
       "   'clusters': 0,\n",
       "   'noise': 10000},\n",
       "  {'labels': array([-1, -1, -1, ..., -1, -1, -1], dtype=int64),\n",
       "   'clusters': 0,\n",
       "   'noise': 10000}],\n",
       " [{'labels': array([-1,  1, -1, ...,  0, -1,  2], dtype=int64),\n",
       "   'clusters': 3,\n",
       "   'noise': 2262},\n",
       "  {'labels': array([-1,  1, -1, ...,  0, -1, -1], dtype=int64),\n",
       "   'clusters': 2,\n",
       "   'noise': 3965},\n",
       "  {'labels': array([-1,  1, -1, ...,  0, -1, -1], dtype=int64),\n",
       "   'clusters': 2,\n",
       "   'noise': 4609},\n",
       "  {'labels': array([-1, -1, -1, ...,  0, -1, -1], dtype=int64),\n",
       "   'clusters': 1,\n",
       "   'noise': 6292},\n",
       "  {'labels': array([-1, -1, -1, ...,  0, -1, -1], dtype=int64),\n",
       "   'clusters': 1,\n",
       "   'noise': 6520}],\n",
       " [{'labels': array([ 0,  0, -1, ...,  1,  1,  1], dtype=int64),\n",
       "   'clusters': 2,\n",
       "   'noise': 423},\n",
       "  {'labels': array([ 0,  0, -1, ...,  2,  1,  1], dtype=int64),\n",
       "   'clusters': 3,\n",
       "   'noise': 625},\n",
       "  {'labels': array([ 0,  0, -1, ...,  2,  1,  1], dtype=int64),\n",
       "   'clusters': 3,\n",
       "   'noise': 881},\n",
       "  {'labels': array([ 1,  1, -1, ...,  0, -1,  2], dtype=int64),\n",
       "   'clusters': 3,\n",
       "   'noise': 1290},\n",
       "  {'labels': array([ 1,  1, -1, ...,  0, -1, -1], dtype=int64),\n",
       "   'clusters': 2,\n",
       "   'noise': 3096}],\n",
       " [{'labels': array([0, 0, 0, ..., 1, 1, 1], dtype=int64),\n",
       "   'clusters': 2,\n",
       "   'noise': 64},\n",
       "  {'labels': array([0, 0, 0, ..., 1, 1, 1], dtype=int64),\n",
       "   'clusters': 2,\n",
       "   'noise': 105},\n",
       "  {'labels': array([ 0,  0, -1, ...,  1,  1,  1], dtype=int64),\n",
       "   'clusters': 2,\n",
       "   'noise': 146},\n",
       "  {'labels': array([ 0,  0, -1, ...,  1,  1,  1], dtype=int64),\n",
       "   'clusters': 2,\n",
       "   'noise': 215},\n",
       "  {'labels': array([ 0,  0, -1, ...,  1,  1,  1], dtype=int64),\n",
       "   'clusters': 2,\n",
       "   'noise': 310}],\n",
       " [{'labels': array([0, 0, 0, ..., 0, 0, 0], dtype=int64),\n",
       "   'clusters': 1,\n",
       "   'noise': 13},\n",
       "  {'labels': array([0, 0, 0, ..., 0, 0, 0], dtype=int64),\n",
       "   'clusters': 1,\n",
       "   'noise': 19},\n",
       "  {'labels': array([0, 0, 0, ..., 0, 0, 0], dtype=int64),\n",
       "   'clusters': 1,\n",
       "   'noise': 24},\n",
       "  {'labels': array([0, 0, 0, ..., 1, 1, 1], dtype=int64),\n",
       "   'clusters': 2,\n",
       "   'noise': 32},\n",
       "  {'labels': array([0, 0, 0, ..., 1, 1, 1], dtype=int64),\n",
       "   'clusters': 2,\n",
       "   'noise': 45}]]"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eps_list = [0.3, 0.4, 0.5, 0.6, 0.7]\n",
    "min_samples_list = [800, 900, 1000, 1100, 1200]\n",
    "\n",
    "params = []\n",
    "\n",
    "for row, eps in enumerate(eps_list):\n",
    "  params_row = []\n",
    "  for col, min_samples in enumerate(min_samples_list):\n",
    "    db = DBSCAN(eps=eps, min_samples=min_samples).fit(X)\n",
    "    labels = db.labels_\n",
    "    n_clusters_ = len(set(labels)) - (1 if -1 in labels else 0)\n",
    "    n_noise_ = list(labels).count(-1)\n",
    "    params_row.append({\n",
    "      \"labels\": labels,\n",
    "      \"clusters\": n_clusters_,\n",
    "      \"noise\": n_noise_\n",
    "    })\n",
    "    print(labels, n_clusters_, n_noise_)\n",
    "  params.append(params_row)\n",
    "    \n",
    "params"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "array([[1., 1., 0., 0., 0.],\n",
       "       [3., 2., 2., 1., 1.],\n",
       "       [2., 3., 3., 3., 2.],\n",
       "       [2., 2., 2., 2., 2.],\n",
       "       [1., 1., 1., 2., 2.]])"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clusters = np.zeros(((len(eps_list), len(min_samples_list))))\n",
    "\n",
    "\n",
    "for row, eps in enumerate(eps_list):\n",
    "  for col, min_samples in enumerate(min_samples_list):\n",
    "    cluster = params[row][col][\"clusters\"]\n",
    "    clusters[row, col] = cluster\n",
    "plt.xticks(np.arange(len(min_samples_list)), labels=min_samples_list)\n",
    "plt.yticks(np.arange(len(eps_list)), labels=eps_list)    \n",
    "plt.title(\"Clusters\")\n",
    "\n",
    "for row in range(len(eps_list)):\n",
    "  for col in range(len(min_samples_list)):\n",
    "    text = plt.text(col, row, clusters[row, col], ha=\"center\", va=\"center\", color=\"w\")\n",
    "\n",
    "plt.imshow(clusters)\n",
    "plt.colorbar()\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "clusters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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BL/5XSikPKr9zT7lLk6pSymu0p6qUUh5W0XuqFfsrQylVphgjOI3N7eVsROQeEdkkIhtF5AsR8ReREBFZICI7rJ/B+eo/LCIxIrJNRPrlK+8oIhusdVNFpMSZX5OqUsqrPDVFtYhEA3cBnYwxrXA9RH84MBFYaIxpDCy03iMiLaz1LYH+wNsicuJOhOm4JiVtbC39S/r7aVJVSnnNiTuq3F3c4ANUFhEfoAqu+fOGAB9b6z8GLrdeDwFmG2OyjDG7gRigi4jUAAKNMUuNayqUWfnaFFupjanmHPTj4DONSmv3/8mG1s1LO4QS+Tyo6OmyyzqfZumlHUKJ+fnmlnYI/8EUj27NdaKqWEfWYSKyMt/7mdaszBhjDojIy8A+XNM4/WqM+VVEIo0xcVadOBGJsNpGA/lnQYy1ynKs16eXl4ieqFJKeVUxL/5PKmqOKmusdAhQHzgMfCUi159hW4Vlc3OG8hLRpKqU8hoP36baF9htjEkEEJFvgR5AvIjUsHqpNYAEq34sUDtf+1q4hgtirdenl5eIjqkqpbzKic3t5Sz2Ad1EpIp1tr4PsAWYC4y26owGfrBezwWGi4ifiNTHdUJquTVUkCEi3aztjMrXpti0p6qU8hrX81Q901M1xvwrIl8Dq4FcYA0wE6gGzBGRm3El3qFW/U0iMgfYbNW/3RjjsDY3HvgIqAzMt5YS0aSqlPIqTz6lyhjzOPD4acVZuHqthdWfQiFn34wxK4FWnohJk6pSymtcY6oVe9RRk6pSyqsq+m2qmlSVUl5TgutUyx1NqkopL9LDf6WU8hhjIEeTqlJKeY72VJVSykN04j+llPIwp579V0opz9Cz/0op5WE6pqqUUp5idExVKaU8xqBjqkop5VHaUy0FEWEBTLpvIKHBVXE6Df/7eR1fz13F+JsupEeXhuTmOjgQd5jnX5/PkaNZADSoF879d1xC1Sp+GGMYc/csxCY89fAQakZVx+k0/LM8hnc++rPQfY4Y2pWBl7TB6TS88c5vrFi9p9hxV/KxM2vsNVTysWO32fh1ww6m/baUpjXCeOzyPlTxq8TB1HQenD2fo1nZADSJCuPxK/pQzd8PpzEMe+tzsnMdfDjmasIDqpKV45qK49b3vyXlaGaBfd5yYWeu6tQKh3Hy3Nzf+XvH3mLHnZ9NhO9uGEH8kSOM+ep7AEZ2bMf1HdvhcDr5feduXly8BICx3TsztG1rHE4nTy9YzF+7Xfse0LwJ43t0xS5ySv3TFdW+JAJ8/Xm6/WAaB0ZgMDyy+gf61mxO76im5Dgd7D+awqTVP5CRcxxfsfNE+0G0ql4TJ4Zn1//MiqQ9+Nt9eb3LUGpXDcFpnCw+tJ1XN/1W6P5ubXI+V9XtgNM4mbJ+Pn8n7CxZ3D7+PNb2choFRGKM4Yl139EjojFX1ulEatZRAN7ctoC/ErbTLawhdzW7BF+bnRyng9e2/MKK5F0ANA+qyVNtr8TP7stfCdt5cdOPhe7vpoa9uLxOR5zGyQubfmRpYkyJ4i4pPVFlEZH+wBu4Zit8zxjzfBH1OuOaA2aYMebrkgblcDh5+73FbN8ZT+XKlXjvjVGsWLOHlWv2MPOjP3A4DeNuvIDrr+nGjA//wG4THr1/IM+88iM7dycSGOBPrsOJr83O7G9XsGb9Pnx8bLw2ZRhdO9bn31W7T9lf3dqh9OnVnNHjPyAstBqvTrmGEWPew+ks3owK2bkObnr3a45l5+Bjs/HJuGtYsm03kwf35qWf/mTl7gNc0aklN/XqyJsLlmK3Cc8P68/Dc35mW1wSQVVccZ/w0Oyf2XQgvsj9NYwIYUDbpgx+bRYRgVV575arGPjyRzhNiWeCYHSn9uxMTqGaXyUAutapTZ/GDbns/U/IdjgIqVIZgEahIQxs3owB735MRLWqfHzt1Vz8zocE+vvxUO9eXPHhZ6RkZvLCoH50r1ubpXv3n7KfotqXNPZJbfrzV3wMdy+fg6/Y8ffxpUrCLl7btBCHcXJfy76MaXI+r2z6jaH1OgAwZNF0QipVZWaPEQz9/V0APtjxD8uT9uArdj44fxQ9IxuxJP7UxNMwIJwBtVpx2cJpRPgH8MF5o7h0wZs4SzADx4MtB/JPwg4eWDUbH7FT2e5Lj4jGfLrrb2bt+vuUuqnZx5iw4lMSszJoGBDB9K43cMlvLwIwufVgnl7/A+sP7+etLqM4L7wxfyfuOKV9g2rh9ItuzVV/TCXcL5B3ut3IkMWvlSjukjIIuc6KfaLqrL+dNYXrNOBSoAVwrTXVa2H1XgB++a9BJaceZftOVzLJzMxm7/5kwkOrsWLNHhxWotu09SDhoQEAdO5Qn517Etm5OxGA9IzjOJ2GrKxc1qzfB0BurpMdO+MJDwsosL/zuzVi4Z9byMl1EBefxoGDh2nepEaJYj+WnQOAj92Gj92GAeqFB7Ny9wEAlu7Yy8WtGgPQo3Fdth9KYltcEgBpx44XK6n0btGQn9ZtI8fh4EBqOvuTD9O6dlSJ4gaICqjGhY0aMGfdhryy6zq0YeayFWQ7XM/yTTnm6i33adKQH7dsJdvhIDYtnb2ph2lTM4ra1YPYnZJKSqar3j979tGvWeMC+yqqfUlU9fGjU2hdvt67GoAc4yAj5zj/JOzEYVxfUutSYomsHAhAw8BwliW6vlhTso+SnnOcVsE1Oe7IYXnSnrxtbD4cR5TVJr+LajTlp9iN5DgdHDh2mH1HU2gTUvx54qr6+NEhtB7f7V8FQK5xkJF7vMj629LjSMzKAGBnRgKVbD742uyE+VWjqo8f6w+7vrjmxa6ld1SBf6JcGNmcXw5sIMfp4GBmKvuPJtOqeq0C9c41J+L2Uh6585XRBYgxxuwyxmQDs3FNtnW6O4FvODkfjEdERQTSuEEkm7fFnVI+4OLWLFvlOvSpHR2MMfDyU0N5743RXHtVlwLbqVbVjx5dG7FqXcFDzPDQABKSMvLeJyZnEBZarUTx2kT45q4RLHlkLEt37GPD/kPsiE+md4sGAPRr3YSo6q7EXi/MFffMm67gqzuv46Zep85v9szQS/jmrhGMu6hrofuKDKzGocMn4z6UdoTIwJLFDTC574W8uPjPUxJ7/ZBgOtWO5uvR1/LZiGtoXSPSte+AAOLSj5zcd8YRoqpVY2/qYRqGhhAdFIhdhIsbN6JGQMEvsqLal0TtqsGkZB3j2Q6X803vsTzdfjCV7b6n1Lmybvu8HufWtHguqtEUu9iIrlKdltVrFkieAb7+9K7RlKUJpx7VAET6B3Io8+TsrvGZ6UT4F0y+Z1OrSjCp2Ud5qu2VzO55G4+1uRx/K+7h9boxp9cdPNHmCgJ8/Qu07VujJVvT4shxOojwDyQ+fzzH04jwL/iZR1QO5NDxtHz10oko5EvjnDKuw393l/LInaQaDeQ/diswfauIRANXADPOtCERGSMiK0VkZU720bPuuLK/L09Pvpw3313IsczsvPKRw7rhcDhZsHgzAHa7jTYtonn65Xnc/uBn9OzemA5t6+TVt9uExx68jG/mriLuUFqB/YgH51J0GsNVUz/joufeo3XtKBpFhvLo179ybbd2zLnjOqr4VSIn12HFZaNDvZo8OHs+I2fMoU/LhnRt6JqX7KHZ87ni9U8YOWMOHepFM7hDwWmxC4vblDDw3o3qk3zsGJsOnfqdaLfZCPL35+qPv+CFRX/yxuWDXPsuZBsGSD+exeO/LOSNywfyxchhxKalkVvIMIonp6+0i40W1Wswe/cKrlr8Dsdys7m1yfl568c26YnDOPnf/vUAfLt3DfGZ6Xx14RgebtOftSn783q0J7b3cqer+HTnv8QeSy0Yu4c+d7vYaBZYgzl7lzN8ydscd2RzU8NezNnzL4MWvcqwP6eRlJXBfc0vPaVdw2oRTGjWj2c2uKZRkkI+zcKiKfQz/w9DRSVxYky1IidVd8ZU3fn7fx14yBjjkEIzlNXINV/3TICAoFpn/L9pt9t4etLlLFi8mT//OTk21L9PS7p3bsg9k7/MK0tIymDtxv2kpbsOOZet3EWThlGsXuc69L//zn7EHkzlqx9WFbqvhKQMIvINC4SHBpCUcqTQuu7KOJ7F8l2xnN+kHh8tWcWYD74FoG5YdS5oVh+A+LQMVu6O5fAx1yHfkm17aBEdwb8795OQ7vrSOZadw0/rttK6VhRzV285ZR+H0o7k9XoBooKq5bUrrg7R0fRp1JALGtTHz8eHan6VePmySzmUcYRftrk+//VxhzDGEFK5MocyMqiRr1ccFVCN+COuz2xRzC4WxbiOIoa1a13okMaZ2hdXfGY68ZnprE91DbH8enBzXlIdUqctF9Zowo1/zcqr7zBOnt9wcpTq8143s/dISt77J9tfxt6jKczamX+K+HyxZ6af0rONrBxI4vGMQuueMe7j6SQcT2fjYdeU8wviNnFTw16k5OtwfLtvJVM7j8x7H+EfyKudruPRtV8TeyzF2k5a3tAGQKR/UKHxxGemE+UflK9eyeL+r8prsnSXOz3VoqZ1za8TMFtE9gBXA2+LyOX/JbCHJvRn7/5k5ny/Mq+sS8f6XHd1Vx5+6luysnLzypev3k3DehH4+flgtwntWtdmz37XOOUtI8+nWlU/3py5sMh9/f1vDH16NcfXx06NyCBqRQezZXtckfWLEly1MgH+fgD4+djp3qgOuxNTCKnqOrkjAmMv6sqX/7p6TH/v2EuTqDD8fV1xd6pfi53xKdhtQvUqrkM+H5uNC5o1YEd8coH9Ld68iwFtm+JrtxMdHEid0GA27D9U7LgBXvnjL3pOe5fe09/n7h9+ZNne/dz/v/n8tj2G7nVdvf56IdXxtdtJycxk4Y5dDGzejEp2O7WCAqkXXJ31B137PnEyK9DfjxEd2p4yRnvCmdoXV1LWEeIy06hXLRSAbuENiMlI5PyIRtzS+HxuW/oFxx05efX97b55wwM9whvgME52ZrjG4yc0v4gAHz+eW/9zkftbHLeNAbVa4WuzE12lOnWrhbI+5UCx407OOsKhzDTqVg0DoGtYQ3YdSSDM7+SXzUVRLYjJcJ1fCPDx580uI5m69VfWpu475fc/lptFa2t8dFCtdvwef+oXMMAf8VvpF90aX5udmpWDqVM1NC+he8uJB6r8f++prgAaW1O6HgCGA9flr2CMqX/itYh8BMwzxnxf0qBat4imf59W7NydwPtvumaafffjJdw1tg+VfO28OuUaADZvjeOVab9y5EgWX36/gpmvjcIYw7KVu1i2YhfhodUYNbwHe/cn895U13a+/d8afvx1Ped1bUTTxlF88Olf7NmXzOK/tjJrxk04HIbX3l5Q7DP/AOEBVXn2mn7YRLCJ8MuG7fyxdTfXn9eea7u1BeC3TTF8t3ITAOmZWXy8ZDVf3nEdxhiWbNvDn9t2U9nXh5k3XYmP3YbdZmNpzD6+Xu5KTL2bN6BlrUjeWrCUnQnJ/Lx+O3PvHYXD6eSZHxb9pzP/hfl63UaeG9iPH28ZRY7DwYPzXMkmJimZ+Vu3Mf/W0eQ6nTzx68l9P3pxb5pFhAPw1l/L2JNyGICLGjWgdY0o3ljyzxnbl8SU9fN5qdNV+Nrs7D+ayuTV3zPnwjFUstl5/7xRAKxLjeXJtfMI8avKez2ux4khITODh1a6jiIi/QMZ16wXOzMS+ab3WAA+37Wcr/eupndUU1oF1+TNLYuJyUjk59hNzOtzOw7j5Ol1P5b4DPoLm+bxbPuh+NrsHDiWwmPrvuWhloNoGhiFAQ4eS807zB9Wrxt1qoQypnFvxjTuDcC4fz8iNfsoUzbM5am2V+Fn9+XvxO38lbAdgAsim9EiKJrp2xey80gCCw5u5NsLJuAwDp7b+D+vnvk/wZTTZOkucWdMRUQG4DrEtwMfGGOmiMg4AGPMjNPqfoQrqZ7xkqqAoFqm/fl3lTDs0pXc2vfslcqg7CDv/wPyFJ9m6WevVEb5+eaevVIZte6yKauMMZ3OXtM9AU2jTPu3R569omVJ35c9un9vcOs6VWPMT8BPp5UVelLKGHPDfw9LKVURGVPxx1TL5B1VSqmKq6If/mtSVUp5keCo4HdUaVJVSnmN3vuvlFKeZFzjqhWZJlWllFeV13v63aVJVSnlNQY9UaWUUh5Ufu+UcpcmVaWUV+mYqlJKeZAe/iullIcYo0lVKaU8SsdUlVLKg3RMVSmlPMQgOPU2VaWU8pwK3lHVpKqU8qL/ByeqKnY/XClV9phiLG4Qkeoi8rWIbBWRLSLSXURCRGSBiOywfgbnq/+wiMSIyDYR6ZevvKOIbLDWTZUzTbh3BppUlVJeZYy4vbjpDeBnY0wzoC2wBZgILDTGNAYWWu8RkRa4poRqCfTHNZ+e3drOdGAM0Nha+pfk99OkqpTyKmPcX85GRAKBXsD7rm2bbGPMYWAI8LFV7WPgcuv1EGC2MSbLGLMbiAG6iEgNINAYs9S45piala9NsZTamKrt6HGq/L2ttHb/n1RZ6VfaIZSIWDO0lkemWpXSDqHEkjqHlHYIZUYJHqgSJiIr872faU11f0IDIBH4UETaAquACUCkMSYOwBgTJyIRVv1oIP/c47FWWY71+vTyYtMTVUop7zFA8ZJq0lkm/vMBOgB3GmP+FZE3sA71i1DYzs0ZyotND/+VUl7lycN/XD3KWGPMv9b7r3El2XjrkB7rZ0K++rXzta8FHLTKaxVSXmyaVJVS3uXBs//GmEPAfhFpahX1ATYDc4HRVtlo4Afr9VxguIj4iUh9XCeklltDBRki0s066z8qX5ti0cN/pZQXCcbp8etU7wQ+E5FKwC7gRlwdxjkicjOwDxgKYIzZJCJzcCXeXOB2Y4zD2s544COgMjDfWopNk6pSynvOwcX/xpi1QGHjrn2KqD8FmFJI+Uqg1X+NR5OqUsq7Kvh9qppUlVJeVrFvU9WkqpTyLu2pKqWUB2lSVUopDyn+xf/ljiZVpZRX6ZP/lVLKkzSpKqWUB+nhv1JKeYgBcZZ2EOeWJlWllBeJ9lSVUsqjdExVKaU8SJOqUkp5kCbVssFmE6b+/hjJB1N5fPhUbnlqKF37tyU3J5eDuxN59fYPOJqWSZMO9ZnwxigARIRPn/+Bf+atKbC9atWrMunDsUTWCSN+XxLP3jCDI2nHPB531cDK3P3qCOo1q4kx8No9n3DegHZ0vaQ1uTkODu5J5NUJn3A0PZPI2iHMXPIYsTvjAdi6ag9vPvhFIbFXYdLMm4msHUr8/mSevfU9jqRlejTuy2/qRf9h3TDGsGdbHK8+MJvaDSO4c8pQfP18cOQ6mfbYN2xft4+A6lWY/PYNNGlTmwXfrGD6498Wus1qQVV4+K2RREaHEH8ghedun8WR9P8e9z1PXUHXXk05nHKUcVe+CcAt9/aj64XNXJ/x/hReffRbjmYcx8fHzl2PD6Fxy5oYp2HG8z+xfuVuABq1qMl9z1yJn58vK5ZsZ/rzPxa6v2E396LflR1xOpxMf/5HVv0TU6K4K/nYeXfiMHx97dhtwsKVO5j5w1ICq/rz3LiB1AgLJC4pnYnT55FxLAsfu41Jo/vSol4UTmN45fPFrNrmmgHEx27jwesvomPT2hhjePvbv1m0akeBfd4woDNDerbGaZy89Nlilm3aW6LYS+z/wcX/bj2kWkT6W9O5xohIgakKRORCEUkTkbXW8pinA718/MXs33byQdyrF29mbPfHGH/eExyIiWfYPQMB2LvlAHde+DS393ySR656jbteG4XNXvDXHHbPpaz9Yws3d5zE2j+2cM09AzwdMgDjnhnKqsWbufX8p7jtoins236I1X9sZewFzzC+9xQO7Exg2F15s+QStzeJ2/s8x+19nis0oQIMu7Mfa5ds4+buT7B2yTauubNfofVKKjQyiCE39OSuwa8xvv9L2Ow2LrisPTc/fBmfvfELdwx8hU9f+5mbJw4CIDsrl09enc97z84943avGX8Ra//ewS0XPcfav3dwzfhCn8xWbAt+WMMj4z8+pWz10p2MveJNxl/1Fgf2JjHsll4AXHq16wlx4698i4fHfMStD/TnxEzEdz4ymKlP/sBNA1+jZt1QOp3fuMC+6jQI54JLWzP28qlMHj+L2x8ZjM1WsiSRnetg3Etfcd3jn3DdE5/So3U9WjWowQ0DOrN8yz6ufPhDlm/Zxw0DugBwxQWtARj+2Cxuf/lr7h52AScmUb5pUFdS049x1aQPGfrIR6zatr/A/urXDOGSrs245tGPufPVb5k4sg+2ks3C/J+IcX8pj86aVK3pW6cBlwItgGutaV5Pt8QY085anvJkkGE1g+l8SRt+/mRJXtnqxZtwOlzXZmxduZOwmq5pvbMys/PKff19MUXcvtF9QHt+++IfAH774h96DGzvyZABqFLNn9bdG/HzZ6795OY4OJqeyeo/tpyMfdVuwmpWL9Z2u/dvw29fuuYu++3LZfS4tK1H4waw221U8vfFZrfh5+9LSkIaxhiqVHNNHlglwJ/k+HTA9ZlvWrmb7KzcM8d9cSt++2aFK+5vVtD9kv/86EoANq7aQ8ZpPfXVS2NOfsbr9hMWGQRAnYbhrP13JwBpKUc5kn6cxi1rEhJWjSrV/NiyzpWMFs5dS4+LCv6Zd+/dnD/mbyAnx0H8gVTi9iXTtHWtAvXclZmVA7h6mj52GwbDBe0bMu/vzQDM+3szF3ZoCED9mqGs2OyKLzUjk4xjWbSoFwXA4J6t+PDH5YDrjqW0I8cL7OuCdg359d+t5OQ6OJiUzv6Ew7RsEFXi2EvMg0/+L4vcOfzvAsQYY3YBiMhsXNO8bj6XgeU39rnhvP/YV1QJKHw20EuuP58/v12R975px/rc+9aNRNQO5aVx7+X948qvekQgKfFpAKTEpxEUHuDxuKPqhpGWfIT73hhJ/Za1iFm/j+mPfEXWseyTsV/Xgz+/X3WyTZ1Q3vrtYY5lHOfj5+eyyUoAp8QeHkBKgiuhpSSkExTm2diT49P45t3fmfX3o2Qfz2H1km2sXrKdxIOHeebjsdwy6TLEZuO+q6cWa7vVwwJITcwAIDUxg6DQah6NuyiXXNGRP3/ZAMCubYfo3rs5v8/fQHhUEI1b1CQ8KgjjNCRZXxIAifFphEYU/FxDIwPZuv5kLzApPp3QiMASx2YT4ZPHR1A7ojpfLVrHpl2HCAmsQnLaUQCS044SHOCaSXbH/kQuaN+QX5dvJTIkgOb1IogMCWDvoVQAxl9xHh2b1SI2IY0XP1tESvqpw1kRwQFs2BmX9z4h9QgR1b3z/+D/E3cO/6OB/McSRU3d2l1E1onIfBFpWdiGRGSMiKwUkZXZzoLfpIXp0q8NhxMziFlX+NjP8PsG4sh1smjOyVlnt63azdjuj3HXRc8w7J4B+PqVztCx3cdGo9a1mffxEu7o+xzHj2Uz7M5L8tYPv7s/jlwHi75x9TBS4tMZ2eER7uj7HDMf/5qJ02/K6xl6U7XAynS7uBU39nqGEd2ewK9KJXpf3pGB15/HzGd+YNR5TzPzme+5+/lhXo+tuIbfegEOh5NF89YB8Mt3q0mMT+PN2eMZ99AANq/bh8PhzBsCyK+wg5zCjpaLOhpyh9MYRjzxKQPue5eW9aNoGB1aZN25SzaSkJrBrMdGcN+1F7I+Jg6Hw4ndLkSFBLAu5iDXP/kZG3Ye5O5rehUSfCGxlzjykvt/f/iPe1O3rgbqGmPaAm8C3xe2IWPMTGNMJ2NMp0o295JFy66N6HZpWz5e/wIT3x9L217NePCdWwDoe20PuvZry4u3vlto2/3b4zh+LJt6zQt+BxxOSCfEOiQMiQwizepBeVLSwcMkHTzMttV7AFjyv9U0al3HFfs1Xel6cStevO3DvPo52blkpLp6KDHr9xO3J5HohhEFtns4MYMQq3cUEhFIWpJnY293fhPi96eQlnIUR66Tf37ZQIsO9eh7ZSf+/nm963f5cR1N29Yp1nYPJ2UQbB0RBIcHkJZ8xKNxn67v4PZ0vaApL078Kq/M6XAy88X53D50Gk/e9RnVAipzcG8ySfFphEWe7HGGRwaRUsjfRNKhdMKtvxuAsMjAQusV15HMLFZt20/3VvVIST9GaFBVAEKDqpKa4epxOpyGV2f/wYgnPuW+N+dSrYof+xJSSTtynMysHBavdp2Y+m3FdprWLfh3k5CSQWTIyZ5pRHA1Eg+f2/8HhTLi/lIOuZNUi5rSNY8xJt0Yc8R6/RPgKyJhngjww6e+ZWTLBxjd5iGev/kd1v25lRfHvkfHPq0YOuFSnrh2KlmZJw+nI+uG5Z2YiqgdSq1GUcTvSy6w3WXz19L32h6AKzkv/angFQL/VWpiOokHU6llJcb2PZuxb3scHXu3YOgdl/DEqBlkZebk1Q8KrZZ30iOqbig1G0QQtzepYOy/rKfvsG6u2Id1Y6mV6Dwl8WAqzdrXxc/fF4B2PRqzf2c8yQnptO7aMK/swJ7EYm132W+b6HtVZ1fcV3Vm6YKNHo07v47nNWboTT154s5PyTp+8jP28/fFr7Lr92rfvSEOh5N9uxJJSTpC5tEsmrVxjY/2GdyOpYu3FPwdft/KBZe2xtfXTmR0MDXrhrJtQ2yJYqweUJlqlf1ccfn60KVFHfYcSuGPNbsYdJ5rPHfQeS34Y41rCMivkg/+lVxHXV1b1MHhcLL7YAoAS9bupGNT1z/Tzi3q5JXn9+faXVzStRm+PnZqhgVSO7I6m3YdKlHsJWYAZzGWckjOdugiIj7AdlyTaB0AVgDXGWM25asTBcQbY4yIdME193Zdc4aNB/mEme7VhhQr2DbnN+WqO/rx+PCpfLD6WXwr+ZKe6vqm3bpiF2/e+wl9hnXnmrsvJTfXgXEaPnvxfyz90ZUw7546mh8/+J0da/cSEFyVSR+NJ6JWCAmxKUwZPZ0jh4+6F4ifn9sxN2hZi7tfHYFvJR/i9ibx6oRZTP3loVNjty6dOm9gO0Y9OAiHw4nT4eSTl37k319dY4F3vzqCHz9ewo51+1yxv3szEdEhJBxIYcot73Hk8NkvB5Mq7g8lXH93P3oNaocj18nOzQd4Y+KXNGlTh7GPXY7dx052Vg7THv2GmI2uhPLRkkeoUs0fH187R9MzmTzqHfbFxDPh+Wv46bN/2LEhloDqVZj01ijCawaTeDCVKbfPcvsyNlOtSpHrJr5wDW061yewehVSU47w6bRFDLulF76VfEi3Ppet6/fz5tNziaxZnSkzRuM0huSEDF577DsS4g4D0LhFTe575ioq+fuy8q/tvP3sPAC6XdiMxi2j+WTaQsA1pHDJFR1x5jqY8eJPrPyr4KVL+SV1Dim0vFGtMJ68uT82m2ATYcGK7bz3v2UEVfXnufGDiAoN4FByBhOnzyP96HFqhAby1n1X4nQaEg4f4ekPf+VQsquXHBUawFO3XEpAFT9SMzJ58oNfiE/JoFe7BjSvF8U737tOlt40qAuDz2+Fw+nklS9+558Ne84Y+6oP71tljClsUr0S8atd29S65x636++6z7P794azJlUAERkAvA7YgQ+MMVNEZByAMWaGiNyBa3rXXCATuNcY88+ZtlmSpFpmFCOpliXFSaplzZmSallXVFItD85JUr27GEn1/vKXVN06g2Md0v90WtmMfK/fAt7ybGhKqQqpnJ6Acle5uaNKKVX+leez+u7SpKqU8q5yelbfXZpUlVLepT1VpZTyHD38V0opT9KkqpRSHqInqpRSysPK6Z1S7tKkqpTyqoreU3XrIdVKKaXcoz1VpZR3VfCeqiZVpZT36IkqpZTyME2qSinlQZpUlVLKM4SKf/ivZ/+VUt7l4dlURcQuImtEZJ71PkREFojIDutncL66D4tIjIhsE5F++co7isgGa91UKWzSMjdpUlVKeU8xJv0rRo92ApB/7puJwEJjTGNgofUeEWkBDAdaAv2Bt0XEbrWZDowBGltL/5L+ippUlVLe5cE5qkSkFjAQeC9f8RDgY+v1x8Dl+cpnG2OyjDG7gRigi4jUAAKNMUutKaBm5WtTbKU2pmocThwZnp/B1CuOuDmXVRkjqeX4OZZ2+9nrlFGhu/efvdL/Ix4eU30deBAIyFcWaYyJAzDGxInIiallo4Fl+erFWmU51uvTy0tEe6pKKe8q3phqmIiszLeMObEZERkEJBhjVrm558J6FeYM5SWiZ/+VUt5TjBNQlqQzTPx3HjDYmpjUHwgUkU+BeBGpYfVSawAJVv1YoHa+9rWAg1Z5rULKS0R7qkopr/LUiSpjzMPGmFrGmHq4TkAtMsZcD8wFRlvVRgM/WK/nAsNFxE9E6uM6IbXcGirIEJFu1ln/UfnaFJv2VJVS3nXur1N9HpgjIjcD+4ChAMaYTSIyB9gM5AK3G2McVpvxwEdAZWC+tZSIJlWllFedi4v/jTG/A79br5OBPkXUmwJMKaR8JdDKE7FoUlVKeVcFv6NKk6pSynuKf6Kq3NGkqpTyGqHw65cqEk2qSinv0p6qUkp5jujEf0op5UHaU1VKKQ/R6VSUUsrDNKkqpZTnaE9VKaU8SZOqUkp5jvZUlVLKU/SOKqWU8jBNqkop5Rn/H6aoLndJtWpQFe59dxz1WtYGY3j5lulsWbYDgKvvvYyxL43kqoibSU8uOP9Vp35tue21G7HZbcx/fyFfvlji59C65b53x9J1YAcOJ6Qzpt0DAAQEV2XyFxOIqhvOob2JPDP8DY4cPkpk3XDe3/gKsdtcDxzf8u8O3rj9/QLbLKq9p907cyzdBrTncGI6Y9o/eMq6q+8ZyJgXrufqGmPyPuf6reswYdrNVAmsgnE6uaP7I+Rk5RSM/bMJRNYNI35vEs9c5/nYw2uF8MB74wiJDMLpNPz0wWK+n/YLPa/swsjJV1KnWU3u7Pk4O1bvBiCyThjvrX2R2O1xAGxZHsPUuz4ssN2A4KpM/uQOIuuGE783kWeuf5Mjh495NHZfP19e+WUSvn4+2H3sLPl+BZ9M+Y6eV3Rm5KQrqN20Bndd8CQ71uzJazPsvkH0H9ULh8PJ9Ac+ZdXCjYXGPunj24isE0b8viSmjJrm8diLQ5wVO6u69eR/EelvzZMdIyITi6hzoYisFZFNIvKHZ8M86bbXb2TlL2u5ueU9jG3/APu2HAAgvFYoHS9uTfzexELb2WzCnW/ezKSBz3JLq3voPfw86jQv8dxebvl11h9MGvjcKWXDHhrCmkUbuaH5PaxZtJHhDw3JW3dwZzzjOk1kXKeJhSbUs7X3pAWz/mDSoOcLlIfXCqFDn1M/Z5vdxkMf3c7UO95nTLsHuL/v0zhycgvG/uAQ1izeyI0t72XN4o0Me3Cwx+N25DqZOfFzbmn/EBMueILBY/tSp1lN9myK5anhb7Dhr20F2sTtimd8t8mM7za50IQKMOz+y1jz+2ZubH0/a37fzLD7L/N47DlZOTw48HnGd3+U8d0fpVPf1jTr3JA9m2N56rqpbPj71NjrNKvJhVd3ZUznSUy+4mXueG00NlvBx5Vcc+9A1vy+mZvaPeSK/d5BHo/dbcWZn6qc5t6zJlVrXuxpwKVAC+Baa/7s/HWqA28Dg40xLbGetO1pVQIq07pnc+a/vwiA3BwHR9Nc37jjXh3Nuw99hmuG2YKadmnEwZ2HOLQ7gdwcB79/+Q89Bnc+F2Hm2bBkKxkpp/bEelzWiQWz/gRgwaw/6TG4qOl3Cvdf27trw19byUg9UqB83MujeG/S5+T/mDte3IbdG/axa/0+ADJSjuAspDfS/bKOLPjEiv2TcxN7yqHDxKzdA0DmkePs23qQsJoh7N92kNgdcSXebvdBHVnw6RIAFny6hB6XnZvP/fjRLAB8fO3Yfe0YY9i/LY7YHYcKxjSwA79//S852bnE703i4K54mnZqUGi93z77C4DfPvuL7oM6nJPY3eWp6VTKKnd6ql2AGGPMLmNMNjAb1/zZ+V0HfGuM2QdgjEngHKjRIIK0xHQe+OA2pq98gXtnjsW/ih/dL+tI8oEUdq3fW2TbsOgQEvcn571POpBMWHTIuQjzjIIjg0g5dBhwJYDqEYF566LqhzN9xXO8sugxWp3frNjtz7VugzqSdCAlL3meUKtxDYwxPDtvItP+fZah9xXeiwuOOC328HMbe2SdMBq1q8vWFTvPWC+qXjhvL32Gl3+dTKvzmhZaJzgi0Cux22zC2/88xZe732TNok1sW7mryLphNYNJjE3Je590IIXQmsEF6gVHBJISnwZASnzaOf/cz6qC91TdGVONBvJPXB4LdD2tThPAV0R+xzX/9hvGmFmnb8iaXnYMgD9Vih2s3cdO4w71mTbhA7Yuj+G2125g5ONDad2zORP7P3PGtq75vE5VVK+2NKTEpTKi/h1kpByhcYf6PPHN/dza5n6OZWSWdmgA+FWuxHUTL2figGcLrLP72GjVoyl39HiErGNZvPDLZHas3sXaxZtKIVIX/6p+PPbFBKY/8OkZP8OUQ4cZ0eRu1+fevh5PzLmHWztMLLXP3ek03NbjMaoGVeHxL+6iboto9m4+UHhlj06s7D3ltQfqLnd6qu78r/MBOgIDgX7AoyLSpEAjY2YaYzoZYzr54lfsYBNjk0mMTWbr8hgA/vxmGY3b1yeqfgTvrHmJT3a+RXitUKavfIHgyKACbcNrh+a9D4sOJflgarFj+K9S49MIiaoOQEhUdQ4npAOQk51LRorrcHvH6t3E7YqnVpMabrc/12o0jCSqXjgzVr7ArO1TCa8Vwtv/PktwZBBJB1JYv2QL6ckZZGVms+LntTRuX79g7AmnxZ54bmK3+9h57IsJLPryH/7+YeUZ657yua/Zw8FdCUQ3jipQLzUh3Suxn3A07Rjrlmylc982RdZJOpBKeK2TR1th0SEkxxX8m05NSCfE+vcQEhl0zmM/qwreU3UnqRY1V/bpdX42xhw1xiQBfwJtPRPiSanxaSTuT85LNu0vas2ONbu5psatjGx4ByMb3kFibDLjOz1EqnW4c8K2FTuJblSDqHrh+PjauXBYD5b+78z/4M6FpfNWcfGoXgBcPKoX/1gxBIUF5J1kiKofQXSjKOJ2xbvd/lzbs3E/19Qax6gmdzGqyV0kxqZwW9dJpMansfLX9dRvXQe/ypWw2W207tmcvVsK9q6W/W8VF4+0Yh/Zi6X/W3VOYr13xi3s23aQb6aefULMUz73euFEN4rk0O6Co1fLflzNxdf3BODi63uydJ7nYw8KC6BqkOsIrpK/Lx16t2D/9qKnn1/20xouvLorvpV8iKwbRnTDyEKHC5b9tIa+I84HoO+I81n642qPx+62YoynltcerTuH/yuAxtY82Qdwza993Wl1fgDeEhEfoBKu4YHXPBnoCdMmfMDDn9yFTyUf4nYn8PJNbxdZN7RGMPe+O5bJg57H6XDy1l0f8Nz8ydjsNn75cDF7N8eeixDzTPr0Ttpc0IKgsAA+3zONWU9+zewXfuDR2Xdz6Y29SdifzNPDXB9T657NGf3EUBy5TpwOJ2/c/h4Zqa6TXPe+M4Z5M39j+6pdRbb3tIc/uZM2vZoTFBbAZ7ve4pOnvubnj34vtO6Rw0f59o2feHPpFDCG5T+vZfn8NQDcM+NW5s1cyI7Vu5j90lwe+XwC/W+4kIT9yTxz7esej7tljyZcPKInuzbsY/oy16SZHzw+h0p+vtz26iiCwgJ45tv72bl+L5MGv0jr85sx6tGrcOQ6cDoMU+/8MO9zv+ftW5j33kJ2rN7N7Jf/xyOf3kn/0Re4Yh8x1eOxh0RW5/6Zt2Kz27DZhD+/Xc6/P6+jx2Udue3l6wkKC+Dpb+5l5/p9TL78ZfZuOcCf3y5n5srncOQ6eOveT/JOEN791k38+P4idqzZw5evzmPyrNvpP6oXCbHJTBk5zeOxF0s5TZbuEnfGFUVkAPA6YAc+MMZMEZFxAMaYGVadB4AbASfwnjHm9TNtM1BCTFdb3/8UfKkRt65EK3OkkMttyg27vbQjKDEpx7H/enTWKmOMxy51qBZa27S69B636//72X0e3b83uHXxvzHmJ+Cn08pmnPb+JeAlz4WmlKqQytAJ4nOh3N1RpZQqx4zOUaWUUh6lSVUppTypYh/9a1JVSnlXeb1Uyl2aVJVS3mPQE1VKKeVJ2lNVSilP0qSqlFKeoU/+V0opTzJGx1SVUsqTtKeqlFKepElVKaU8xIA4KnZW1aSqlPKuip1TNakqpbyroo+pls8Hgyqlyq8TVwC4s5yFiNQWkcUiskVENonIBKs8REQWiMgO62dwvjYPi0iMiGwTkX75yjuKyAZr3VQpbGI7N2hSVUp5lYenU8kF7jPGNAe6AbeLSAtgIrDQGNMYWGi9x1o3HGgJ9AfeFpETTxGfjmti0sbW0r8kv58mVaWU9xRn0j83kqoxJs4Ys9p6nQFswTUD9BDgY6vax8Dl1ushwGxjTJYxZjcQA3QRkRpAoDFmqXFNhzIrX5tiKd0x1fJ6EbBxlHYEJWLK83Msc3NLO4ISK6d/5eeE646qYn0iYSKSf3bLmcaYmYVuW6Qe0B74F4g0xsSBK/GKSIRVLRpYlq9ZrFWWY70+vbzY9ESVUsq7ivflnuTOHFUiUg34BrjbGJN+huHQwlaYM5QXmyZVpZRXFbOnevbtifjiSqifGWO+tYrjRaSG1UutAZyYdzwWqJ2veS3goFVeq5DyYtMxVaWU93h4TNU6Q/8+sMUY82q+VXOB0dbr0cAP+cqHi4ifiNTHdUJquTVUkCEi3axtjsrXpli0p6qU8iKDOD3aUz0PGAlsEJG1Vtkk4HlgjojcDOwDhgIYYzaJyBxgM64rB243Ju8kyXjgI6AyMN9aik2TqlLKuzx4+G+M+YvCx0MB+hTRZgowpZDylUCr/xqTJlWllPfoFNVKKeVh5fVSSjdpUlVKeVfFzqmaVJVS3uXpS6rKGk2qSinv0qSqlFIeYijuHVXljiZVpZTXCEYP/5VSyqM0qSqllIcYQOeoUkopz9HDf6WU8iRNqkop5SnuzT1VnmlSVUp5j0GTally3/vj6TqwI4cT0hjT5j4ARj81jB6DO2OchsMJabx04zSS41ILtO3Urx23vX4jNruN+e8v5MsXvi/12Bu0qcuE6WOoXM2fQ3sSeP76qRzLyCxTsYfXCuXBj+8gJKo6Tqfhp3d/47upP+Wtv/q+yxj70iiuCr+J9OSMMhW7r58vr/7xFL5+Pth97Cz5ZhmznpjDrS+OpNugjuRm53JwZzwv3zSNo2nHylTsJ9hsNqateJ6kAyk8Ovh5Rj4+lAG39CUtMR2ADyZ/zvL5awq0KwuxF6mCX6fq1kOqRaS/NZ1rjIhMLGT9AyKy1lo2iohDREI8HeyvH/3OpEtPfWLXVy/NZWy7+xnX4QGW/biK6x+7ukA7m83GnW/dzKQBU7il5T30Hn4edZrXKlDvXCos9nvfHcf7D3/GmLb38ff3yxn6wOAC7Uo7dkeug3fun8XNLe/hru6TGHxbv7z9h9cKpWPfNsTvTSy0bWnHnpOVwwN9nmRc+wcY1/4BOvVrR/OujVm9YB23tr6Xse3u58COg1z78BVlLvYTrpgwgH1bDpxS9s3r8xjX4QHGdXig0IRaVmIvihjj9lIenTWpWtO3TgMuBVoA11rTvOYxxrxkjGlnjGkHPAz8YYxJ8XSwG5ZsISPlyCll+Xt2/lX9Cj2yaNqlEQdjDnFodwK5Obn8/uXf9Bhy1mlvPKqw2Gs1rcn6PzcDsHrBenpe2a1Au9KOPeXQYWLW7AYg88hx9m05QFi06/ty3Ks38O5Dn2KK+OMv7dgBjh89DoCPrx0fXzvGGFYtWI/T4eoubVm2g7Do0DIZe1h0CF0HdGD++wuL1a4sxH5Gxri/lEPu9FS7ADHGmF3GmGxgNq5pXotyLfCFJ4Jz143PXMtne6dz0XU9+fixLwusD4sOITE2Oe99UmxKof+QvG3Pxv10H+z6Y+81tDvhtQvGVJZij6wbTqP29dn67w66X9aJ5IMp7Fq/t8j6ZSF2m83GjNUv8VX8+6z+bT1bl8ecsr7fjb1Z8XPB3l5ZiH38azfy7kOf4nSeerw85Pb+vLP2Ze57fzzVqlct0K4sxF4kAziN+0s55E5SjQb253tf5NStIlIF6I9rEq7C1o8RkZUisjKHrOLGWqQPH/mCEXXHs+jzJQy5o38h+y3YpqjelTe9cvPbDLmtP9NWvEDlAH9yswtOw1xWYvev6s9jX9/P9Hs+xJHr4NpJV/JRIV9g+ZWF2J1OJ+M6PMC1tcfStHMj6rU8OefbdZOuxJHrZOFnSwq0K+3Yuw7swOHENHas3nVK+f+m/8roRncyrv0DpMQdZuwrowq0Le3Yz6wYvdQyE3PxuJNUizN162XA30Ud+htjZhpjOhljOvni526Mblv0+V+cf2XXAuWJsSmE1zr5TR1WK4Tkgx4fnSi2/dsOMrH/M9ze+SEWf/E3B3fGF6hTFmK3+9h5/Ov7WPT5Ev76bjk1GkYRVT+Cd9a+xCe7phFeK5Tpq14kOLJ6mYv9hKNpx1j3xyY69W8HwMWjLqDrwI48f/0bhdYv7dhbnteM7pd14pNd05j8xT20u6gVD826k8MJaTidToxxnTRs2rlRmYv9rDSpFjmla2GG4+VD/+hGUXmvuw/uxP6tBUPbtiKG6MY1iKoXgY+vDxcOO4+lc1d6M8xCVQ8PBEBEGDH5Kua982uBOmUh9vveG8++rQf45rV5AOzZuI9rom5hZIPbGdngdhJjkxnf8UFS4w+XqdiDwgKpGlQFgEr+lejQpw37tx6gU792DHvwch4b8gJZmdmFti3t2D+Y9DnX1RnHyAa3M+Xa11i7aCMvjHqTkKjqeXXOu6ILezbuL9C2tGM/IwM4nO4v5ZA7l1StABpb07kewJU4rzu9kogEARcA13s0wnwmfTaBNhe2JCgsgM/3zWDWE3Pocml7ajWtiXEa4vcm8sb4dwEIrRHMve+OY/Kg53A6nLx15/s89/NkbHYbv3y4mL2bY89VmG7HXrmaP4Nv6wfAX98t55cPF5e52Fue14yLR13ArvV7mbH6JaDoy3jKWuwhNarz4Ed3YLPbEJvw51dL+ffH1Xy0/U18/Xx44ddHAdjy73beGP9umYq9KLe+MJKG7ephjCF+TyKvj3sHKFuf+5kZMOUzWbpL3BlrEZEBwOuAHfjAGDNFRMYBGGNmWHVuAPobY4a7s+NACTFdpdDJDpVSZcRv5utVxhiPXToQ5BdpetQo0Ccr0s97X/fo/r3BrYv/jTE/AT+dVjbjtPcf4ZozWymlCnfi7H8FVq7uqFJKVQDl9ASUuzSpKqW8S5OqUkp5Svm9VMpdmlSVUt5jAGfFPvuvSVUp5V3aU1VKKQ/SpKqUUh5iDMbhKO0ozilNqkop79LrVJVSyoP08F8ppTzEGD37r5RSHqU9VaWU8hyjPVWllPIUvaNKKaU8R59SpZRSHlbBH1KtSVUp5TUGMNpTVUopD9E7qpRSysMq+OG/W3NUnZMdiyQCe8/hLsKApHO4/XOlvMYNGntpONdx1zXGhHtqYyLyM66Y3ZVkjOnvqf17Q6kl1XNNRFaWtwnDoPzGDRp7aSivcVdkttIOQCmlKhJNqkop5UEVOanOLO0ASqi8xg0ae2kor3FXWBV2TFUppUpDRe6pKqWU12lSVUopDyq3SVVE7hGRTSKyUUS+EBF/EQkRkQUissP6GZyv/sMiEiMi20SkXynGPcGKeZOI3G2Vlcm4ReQDEUkQkY35yoodq4h0FJEN1rqpIiKlFPtQ63N3ikin0+qX9dhfEpGtIrJeRL4TkeplMXYFGGPK3QJEA7uBytb7OcANwIvARKtsIvCC9boFsA7wA+oDOwF7KcTdCtgIVMF1N9tvQOOyGjfQC+gAbMxXVuxYgeVAd0CA+cClpRR7c6Ap8DvQKV95eYj9EsDHev1CWf3cdTHlt6eKKylVFhEfXEnqIDAE+Nha/zFwufV6CDDbGJNljNkNxABdvBsu4PpHvcwYc8wYkwv8AVxBGY3bGPMnkHJacbFiFZEaQKAxZqlx/Uufla+NV2M3xmwxxmwrpHp5iP1X628GYBlQqyzGrsrp4b8x5gDwMrAPiAPSjDG/ApHGmDirThwQYTWJBvbn20SsVeZtG4FeIhIqIlWAAUBtyn7c+RU31mjr9enlZUl5i/0mXD1PKH+xV3jlMqla43hDcB3u1ASqisj1Z2pSSJnXryUzxmzBdei2APgZ12Fb7hmalIm43VRUrOXhdyg3sYvIZFx/M5+dKCqkWpmM/f+LcplUgb7AbmNMojEmB/gW6AHEW4c9WD8TrPqxuHqEJ9TCNVzgdcaY940xHYwxvXAd4u2gHMSdT3FjjeXkoWr+8rKkXMQuIqOBQcAI65Aeykns/5+U16S6D+gmIlWsM5p9gC3AXGC0VWc08IP1ei4wXET8RKQ+rpNDy70cMwAiEmH9rANcCXxBOYg7n2LFag0RZIhIN+v/1ah8bcqKMh+7iPQHHgIGG2OO5VtV5mP/f6e0z5SVdAGeBLbiGqf8BNfZz1BgIa7e30IgJF/9ybjOjG6jFM+CAkuAzbgO/ftYZWUyblwJPw7IwdXzubkksQKdrP9PO4G3sO7kK4XYr7BeZwHxwC/lKPYYXGOna61lRlmMXRejt6kqpZQnldfDf6WUKpM0qSqllAdpUlVKKQ/SpKqUUh6kSVUppTxIk6pSSnmQJlWllPKg/wP49e7YXExdxgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "array([[ 7409.,  8057., 10000., 10000., 10000.],\n",
       "       [ 2262.,  3965.,  4609.,  6292.,  6520.],\n",
       "       [  423.,   625.,   881.,  1290.,  3096.],\n",
       "       [   64.,   105.,   146.,   215.,   310.],\n",
       "       [   13.,    19.,    24.,    32.,    45.]])"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "noises = np.zeros(((len(eps_list), len(min_samples_list))))\n",
    "\n",
    "\n",
    "for row, eps in enumerate(eps_list):\n",
    "  for col, min_samples in enumerate(min_samples_list):\n",
    "    noise = params[row][col][\"noise\"]\n",
    "    noises[row, col] = noise\n",
    "plt.xticks(np.arange(len(min_samples_list)), labels=min_samples_list)\n",
    "plt.yticks(np.arange(len(eps_list)), labels=eps_list)    \n",
    "plt.title(\"Noises\")\n",
    "\n",
    "for row in range(len(eps_list)):\n",
    "  for col in range(len(min_samples_list)):\n",
    "    text = plt.text(col, row, noises[row, col], ha=\"center\", va=\"center\", color=\"w\")\n",
    "\n",
    "plt.imshow(noises)\n",
    "plt.colorbar()\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "noises"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "array([[0.19910904, 0.10370166,        nan,        nan,        nan],\n",
       "       [0.38038337, 0.37523856, 0.29062071, 0.35683238, 0.32518975],\n",
       "       [0.46421312, 0.52823868, 0.50607465, 0.46489476, 0.48362532],\n",
       "       [0.52243749, 0.51197996, 0.50695723, 0.48808516, 0.47293348],\n",
       "       [0.33370725, 0.33239   , 0.32189739, 0.51808347, 0.51645263]])"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "silhouettes = np.zeros(((len(eps_list), len(min_samples_list))))\n",
    "\n",
    "for row, eps in enumerate(eps_list):\n",
    "  for col, min_samples in enumerate(min_samples_list):\n",
    "    try:\n",
    "      silhouettes[row, col] = metrics.silhouette_score(X, params[row][col][\"labels\"])\n",
    "    except Exception as err:\n",
    "      silhouettes[row, col] = None\n",
    "\n",
    "plt.xticks(np.arange(len(min_samples_list)), labels=min_samples_list)\n",
    "plt.yticks(np.arange(len(eps_list)), labels=eps_list)    \n",
    "plt.title(\"Noises\")\n",
    "\n",
    "for row in range(len(eps_list)):\n",
    "  for col in range(len(min_samples_list)):\n",
    "    value = \"%.5f\" % silhouettes[row, col]\n",
    "    text = plt.text(col, row, value, ha=\"center\", va=\"center\", color=\"w\")\n",
    "\n",
    "plt.imshow(silhouettes)\n",
    "plt.colorbar()\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "silhouettes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 结果\n",
    "\n",
    "\n",
    "eps基本0.5已经是最好了，高低都会有很差的影响\n",
    "\n",
    "\n",
    "min_sample的值如果是900，应该会比1000有更好的效果"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "db = DBSCAN(eps=0.5, min_samples=900).fit(X)\n",
    "labels = db.labels_\n",
    "n_clusters_ = len(set(labels)) - (1 if -1 in labels else 0)\n",
    "n_noise_ = list(labels).count(-1)\n",
    "\n",
    "unique_labels = set(labels)\n",
    "core_samples_mask = np.zeros_like(labels, dtype=bool)\n",
    "core_samples_mask[db.core_sample_indices_] = True\n",
    "\n",
    "colors = [plt.cm.Spectral(each) for each in np.linspace(0, 1, len(unique_labels))]\n",
    "for k, col in zip(unique_labels, colors):\n",
    "    if k == -1:\n",
    "        # Black used for noise.\n",
    "        col = [0, 0, 0, 1]\n",
    "\n",
    "    class_member_mask = labels == k\n",
    "\n",
    "    xy = X[class_member_mask & core_samples_mask]\n",
    "    plt.plot(\n",
    "        xy[:, 0],\n",
    "        xy[:, 1],\n",
    "        \"o\",\n",
    "        markerfacecolor=tuple(col),\n",
    "        # markeredgecolor=\"k\",\n",
    "        markersize=2,\n",
    "    )\n",
    "\n",
    "    xy = X[class_member_mask & ~core_samples_mask]\n",
    "    plt.plot(\n",
    "        xy[:, 0],\n",
    "        xy[:, 1],\n",
    "        \"o\",\n",
    "        markerfacecolor=tuple(col),\n",
    "        # markeredgecolor=\"k\",\n",
    "        markersize=2,\n",
    "    )\n",
    "\n",
    "plt.title(f\"Estimated number of clusters: {n_clusters_}\")\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.6.13 ('ml')",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.13"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "6742c862b96c2de32cd1408b9158ac0b6c20b04482f05f77e946eadeba80b0ac"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
